model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_base.py

@@ -170,9 +170,9 @@ class Image(NWBData):
     description: Optional[str] = Field(None, description="""Description of the image.""")
     value: Optional[
         Union[
-            NDArray[Shape["* x, * y"], float],
+            NDArray[Shape["* x, * y"], float | int],
-            NDArray[Shape["* x, * y, 3 r_g_b"], float],
+            NDArray[Shape["* x, * y, 3 r_g_b"], float | int],
-            NDArray[Shape["* x, * y, 4 r_g_b_a"], float],
+            NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int],
         ]
     ] = Field(None)
 
@@ -333,13 +333,16 @@ class ProcessingModule(NWBContainer):
         {"from_schema": "core.nwb.base", "tree_root": True}
     )
 
-    value: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    name: str = Field(...)
+    description: str = Field(
+        ..., description="""Description of this collection of processed data."""
+    )
+    value: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    name: str = Field(...)
 
 
 class Images(NWBDataInterface):
@@ -353,7 +356,7 @@ class Images(NWBDataInterface):
 
     name: str = Field("Images", json_schema_extra={"linkml_meta": {"ifabsent": "string(Images)"}})
     description: str = Field(..., description="""Description of this collection of images.""")
-    image: List[Image] = Field(..., description="""Images stored in this collection.""")
+    image: List[str] = Field(..., description="""Images stored in this collection.""")
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_behavior.py

@@ -213,6 +213,16 @@ class SpatialSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "meters",
         description="""Base unit of measurement for working with the data. The default value is 'meters'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -220,8 +230,8 @@ class SpatialSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -235,10 +245,13 @@ class BehavioralEpochs(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[IntervalSeries]] = Field(
+    name: str = Field(
+        "BehavioralEpochs",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEpochs)"}},
+    )
+    value: Optional[Dict[str, IntervalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "IntervalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralEvents(NWBDataInterface):
@@ -250,10 +263,13 @@ class BehavioralEvents(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralEvents",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEvents)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralTimeSeries(NWBDataInterface):
@@ -265,10 +281,13 @@ class BehavioralTimeSeries(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralTimeSeries",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralTimeSeries)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class PupilTracking(NWBDataInterface):
@@ -280,10 +299,12 @@ class PupilTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "PupilTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(PupilTracking)"}}
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class EyeTracking(NWBDataInterface):
@@ -295,10 +316,12 @@ class EyeTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "EyeTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(EyeTracking)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class CompassDirection(NWBDataInterface):
@@ -310,10 +333,13 @@ class CompassDirection(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "CompassDirection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(CompassDirection)"}},
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Position(NWBDataInterface):
@@ -325,10 +351,12 @@ class Position(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "Position", json_schema_extra={"linkml_meta": {"ifabsent": "string(Position)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_ecephys.py

@@ -190,11 +190,12 @@ class ElectricalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        NDArray[Shape["* num_times"], float],
+        None,
-        NDArray[Shape["* num_times, * num_channels"], float],
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        NDArray[Shape["* num_times, * num_channels, * num_samples"], float],
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    ] = Field(..., description="""Recorded voltage data.""")
+    )
+    data: ElectricalSeriesData = Field(..., description="""Recorded voltage data.""")
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -207,11 +208,6 @@ class ElectricalSeries(TimeSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -249,6 +245,41 @@ class ElectricalSeries(TimeSeries):
     )
 
 
+class ElectricalSeriesData(ConfiguredBaseModel):
+    """
+    Recorded voltage data.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Base unit of measurement for working with the data. This value is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and 'channel_conversion' (if present).""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_channels"], float | int],
+            NDArray[Shape["* num_times, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class SpikeEventSeries(ElectricalSeries):
     """
     Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).
@@ -259,15 +290,17 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: SpikeEventSeriesData = Field(..., description="""Spike waveforms.""")
-        NDArray[Shape["* num_events, * num_samples"], float],
-        NDArray[Shape["* num_events, * num_channels, * num_samples"], float],
-    ] = Field(..., description="""Spike waveforms.""")
     timestamps: NDArray[Shape["* num_times"], float] = Field(
         ...,
         description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
+        None,
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
+    )
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -280,11 +313,6 @@ class SpikeEventSeries(ElectricalSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -317,6 +345,40 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
 
+class SpikeEventSeriesData(ConfiguredBaseModel):
+    """
+    Spike waveforms.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Unit of measurement for waveforms, which is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_events, * num_samples"], float | int],
+            NDArray[Shape["* num_events, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class FeatureExtraction(NWBDataInterface):
     """
     Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.
@@ -415,10 +477,12 @@ class EventWaveform(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[SpikeEventSeries]] = Field(
+    name: str = Field(
+        "EventWaveform", json_schema_extra={"linkml_meta": {"ifabsent": "string(EventWaveform)"}}
+    )
+    value: Optional[Dict[str, SpikeEventSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpikeEventSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class FilteredEphys(NWBDataInterface):
@@ -430,10 +494,12 @@ class FilteredEphys(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field(
+        "FilteredEphys", json_schema_extra={"linkml_meta": {"ifabsent": "string(FilteredEphys)"}}
+    )
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class LFP(NWBDataInterface):
@@ -445,10 +511,10 @@ class LFP(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field("LFP", json_schema_extra={"linkml_meta": {"ifabsent": "string(LFP)"}})
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ElectrodeGroup(NWBContainer):
@@ -591,7 +657,9 @@ class Clustering(NWBDataInterface):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 ElectricalSeries.model_rebuild()
+ElectricalSeriesData.model_rebuild()
 SpikeEventSeries.model_rebuild()
+SpikeEventSeriesData.model_rebuild()
 FeatureExtraction.model_rebuild()
 EventDetection.model_rebuild()
 EventWaveform.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_epoch.py

@@ -247,9 +247,6 @@ class TimeIntervals(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class TimeIntervalsTimeseries(VectorData):

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_file.py

@@ -211,28 +211,28 @@ class NWBFile(NWBContainer):
         ...,
         description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""",
     )
-    acquisition: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    acquisition: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    analysis: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    analysis: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    scratch: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    scratch: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    processing: Optional[List[ProcessingModule]] = Field(
+    processing: Optional[Dict[str, ProcessingModule]] = Field(
         None,
         description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ProcessingModule"}]}},
@@ -250,6 +250,9 @@ class NWBFile(NWBContainer):
         description="""Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.""",
     )
     units: Optional[Units] = Field(None, description="""Data about sorted spike units.""")
+    specifications: Optional[dict] = Field(
+        None, description="""Nested dictionary of schema specifications"""
+    )
 
 
 class NWBFileStimulus(ConfiguredBaseModel):
@@ -265,12 +268,12 @@ class NWBFileStimulus(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "stimulus", "ifabsent": "string(stimulus)"}
         },
     )
-    presentation: Optional[List[TimeSeries]] = Field(
+    presentation: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Stimuli presented during the experiment.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
     )
-    templates: Optional[List[TimeSeries]] = Field(
+    templates: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
@@ -348,11 +351,11 @@ class NWBFileGeneral(ConfiguredBaseModel):
         None,
         description="""Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc.""",
     )
-    nwb_container: Optional[List[NWBContainer]] = Field(
+    nwb_container: Optional[Dict[str, NWBContainer]] = Field(
         None,
         description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
     )
-    devices: Optional[List[Device]] = Field(
+    devices: Optional[Dict[str, Device]] = Field(
         None,
         description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "Device"}]}},
@@ -367,12 +370,12 @@ class NWBFileGeneral(ConfiguredBaseModel):
     intracellular_ephys: Optional[GeneralIntracellularEphys] = Field(
         None, description="""Metadata related to intracellular electrophysiology."""
     )
-    optogenetics: Optional[List[OptogeneticStimulusSite]] = Field(
+    optogenetics: Optional[Dict[str, OptogeneticStimulusSite]] = Field(
         None,
         description="""Metadata describing optogenetic stimuluation.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "OptogeneticStimulusSite"}]}},
     )
-    optophysiology: Optional[List[ImagingPlane]] = Field(
+    optophysiology: Optional[Dict[str, ImagingPlane]] = Field(
         None,
         description="""Metadata related to optophysiology.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImagingPlane"}]}},
@@ -450,12 +453,12 @@ class GeneralExtracellularEphys(ConfiguredBaseModel):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
-        None, description="""Physical group of electrodes."""
-    )
     electrodes: Optional[ExtracellularEphysElectrodes] = Field(
         None, description="""A table of all electrodes (i.e. channels) used for recording."""
     )
+    value: Optional[Dict[str, ElectrodeGroup]] = Field(
+        None, description="""Physical group of electrodes."""
+    )
 
 
 class ExtracellularEphysElectrodes(DynamicTable):
@@ -525,8 +528,14 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    group: List[ElectrodeGroup] = Field(
+    group: VectorData[NDArray[Any, ElectrodeGroup]] = Field(
-        ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
+        ...,
+        description="""Reference to the ElectrodeGroup this electrode is a part of.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
     )
     group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
@@ -583,9 +592,6 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class GeneralIntracellularEphys(ConfiguredBaseModel):
@@ -608,12 +614,12 @@ class GeneralIntracellularEphys(ConfiguredBaseModel):
         None,
         description="""Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries.""",
     )
-    intracellular_electrode: Optional[List[IntracellularElectrode]] = Field(
-        None, description="""An intracellular electrode."""
-    )
     sweep_table: Optional[SweepTable] = Field(
         None, description="""The table which groups different PatchClampSeries together."""
     )
+    value: Optional[Dict[str, IntracellularElectrode]] = Field(
+        None, description="""An intracellular electrode."""
+    )
 
 
 class NWBFileIntervals(ConfiguredBaseModel):
@@ -639,7 +645,7 @@ class NWBFileIntervals(ConfiguredBaseModel):
     invalid_times: Optional[TimeIntervals] = Field(
         None, description="""Time intervals that should be removed from analysis."""
     )
-    time_intervals: Optional[List[TimeIntervals]] = Field(
+    value: Optional[Dict[str, TimeIntervals]] = Field(
         None,
         description="""Optional additional table(s) for describing other experimental time intervals.""",
     )

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_icephys.py

@@ -262,11 +262,21 @@ class PatchClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         ...,
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
     )
-    value: Optional[NDArray[Shape["* num_times"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
         None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
     )
 
@@ -281,12 +291,12 @@ class CurrentClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     bias_current: Optional[float] = Field(None, description="""Bias current, in amps.""")
     bridge_balance: Optional[float] = Field(None, description="""Bridge balance, in ohms.""")
     capacitance_compensation: Optional[float] = Field(
         None, description="""Capacitance compensation, in farads."""
     )
+    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     stimulus_description: str = Field(
         ..., description="""Protocol/stimulus name for this patch-clamp dataset."""
     )
@@ -354,12 +364,24 @@ class CurrentClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IZeroClampSeries(CurrentClampSeries):
@@ -512,6 +534,16 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["amperes"] = Field(
         "amperes",
         description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -519,7 +551,9 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
         },
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class VoltageClampSeries(PatchClampSeries):
@@ -532,13 +566,13 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     capacitance_fast: Optional[VoltageClampSeriesCapacitanceFast] = Field(
         None, description="""Fast capacitance, in farads."""
     )
     capacitance_slow: Optional[VoltageClampSeriesCapacitanceSlow] = Field(
         None, description="""Slow capacitance, in farads."""
     )
+    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     resistance_comp_bandwidth: Optional[VoltageClampSeriesResistanceCompBandwidth] = Field(
         None, description="""Resistance compensation bandwidth, in hertz."""
     )
@@ -610,27 +644,6 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
 
-class VoltageClampSeriesData(ConfiguredBaseModel):
-    """
-    Recorded current.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
-
-    name: Literal["data"] = Field(
-        "data",
-        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
-    )
-    unit: Literal["amperes"] = Field(
-        "amperes",
-        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
-        },
-    )
-    value: Any = Field(...)
-
-
 class VoltageClampSeriesCapacitanceFast(ConfiguredBaseModel):
     """
     Fast capacitance, in farads.
@@ -683,6 +696,39 @@ class VoltageClampSeriesCapacitanceSlow(ConfiguredBaseModel):
     value: float = Field(...)
 
 
+class VoltageClampSeriesData(ConfiguredBaseModel):
+    """
+    Recorded current.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["amperes"] = Field(
+        "amperes",
+        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
+        },
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class VoltageClampSeriesResistanceCompBandwidth(ConfiguredBaseModel):
     """
     Resistance compensation bandwidth, in hertz.
@@ -887,12 +933,24 @@ class VoltageClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IntracellularElectrode(NWBContainer):
@@ -942,18 +1000,15 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: VectorData[NDArray[Any, int]] = Field(
+    series: VectorData[NDArray[Any, PatchClampSeries]] = Field(
         ...,
-        description="""Sweep number of the PatchClampSeries in that row.""",
+        description="""The PatchClampSeries with the sweep number in that row.""",
         json_schema_extra={
             "linkml_meta": {
                 "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
             }
         },
     )
-    series: List[PatchClampSeries] = Field(
-        ..., description="""The PatchClampSeries with the sweep number in that row."""
-    )
     series_index: Named[VectorIndex] = Field(
         ...,
         description="""Index for series.""",
@@ -966,6 +1021,15 @@ class SweepTable(DynamicTable):
             }
         },
     )
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
+        ...,
+        description="""Sweep number of the PatchClampSeries in that row.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -976,9 +1040,6 @@ class SweepTable(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild
@@ -991,9 +1052,9 @@ IZeroClampSeries.model_rebuild()
 CurrentClampStimulusSeries.model_rebuild()
 CurrentClampStimulusSeriesData.model_rebuild()
 VoltageClampSeries.model_rebuild()
-VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesCapacitanceFast.model_rebuild()
 VoltageClampSeriesCapacitanceSlow.model_rebuild()
+VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesResistanceCompBandwidth.model_rebuild()
 VoltageClampSeriesResistanceCompCorrection.model_rebuild()
 VoltageClampSeriesResistanceCompPrediction.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_image.py

@@ -152,7 +152,7 @@ class GrayscaleImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -174,7 +174,7 @@ class RGBImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -204,7 +204,7 @@ class RGBAImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -234,12 +234,9 @@ class ImageSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -250,8 +247,9 @@ class ImageSeries(TimeSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -290,6 +288,39 @@ class ImageSeries(TimeSeries):
     )
 
 
+class ImageSeriesData(ConfiguredBaseModel):
+    """
+    Binary data representing images across frames.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, * z"], float | int],
+        ]
+    ] = Field(None)
+
+
 class ImageSeriesExternalFile(ConfiguredBaseModel):
     """
     Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.
@@ -331,12 +362,9 @@ class ImageMaskSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -347,8 +375,9 @@ class ImageMaskSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -409,12 +438,9 @@ class OpticalSeries(ImageSeries):
         None,
         description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""",
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -425,8 +451,9 @@ class OpticalSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -475,10 +502,8 @@ class IndexSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IndexSeriesData = Field(
-        ...,
+        ..., description="""Index of the frame in the referenced ImageSeries."""
-        description="""Index of the frame in the referenced ImageSeries.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     indexed_timeseries: Union[ImageSeries, str] = Field(
         ...,
@@ -526,13 +551,45 @@ class IndexSeries(TimeSeries):
     )
 
 
+class IndexSeriesData(ConfiguredBaseModel):
+    """
+    Index of the frame in the referenced ImageSeries.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 GrayscaleImage.model_rebuild()
 RGBImage.model_rebuild()
 RGBAImage.model_rebuild()
 ImageSeries.model_rebuild()
+ImageSeriesData.model_rebuild()
 ImageSeriesExternalFile.model_rebuild()
 ImageMaskSeries.model_rebuild()
 OpticalSeries.model_rebuild()
 IndexSeries.model_rebuild()
+IndexSeriesData.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_misc.py

@@ -251,6 +251,16 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "see ",
         description="""Since there can be different units for different features, store the units in 'feature_units'. The default value for this attribute is \"see 'feature_units'\".""",
@@ -258,8 +268,8 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -274,10 +284,8 @@ class AnnotationSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], str] = Field(
+    data: AnnotationSeriesData = Field(
-        ...,
+        ..., description="""Annotations made during an experiment."""
-        description="""Annotations made during an experiment.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -316,6 +324,39 @@ class AnnotationSeries(TimeSeries):
     )
 
 
+class AnnotationSeriesData(ConfiguredBaseModel):
+    """
+    Annotations made during an experiment.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], str]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class IntervalSeries(TimeSeries):
     """
     Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.
@@ -326,10 +367,8 @@ class IntervalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IntervalSeriesData = Field(
-        ...,
+        ..., description="""Use values >0 if interval started, <0 if interval ended."""
-        description="""Use values >0 if interval started, <0 if interval ended.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -368,6 +407,39 @@ class IntervalSeries(TimeSeries):
     )
 
 
+class IntervalSeriesData(ConfiguredBaseModel):
+    """
+    Use values >0 if interval started, <0 if interval ended.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class DecompositionSeries(TimeSeries):
     """
     Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -443,24 +515,36 @@ class DecompositionSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         "no unit",
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"ifabsent": "string(no unit)"}},
     )
-    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float | int]] = (
-        None,
+        Field(
-        json_schema_extra={
+            None,
-            "linkml_meta": {
+            json_schema_extra={
-                "array": {
+                "linkml_meta": {
-                    "dimensions": [
+                    "array": {
-                        {"alias": "num_times"},
+                        "dimensions": [
-                        {"alias": "num_channels"},
+                            {"alias": "num_times"},
-                        {"alias": "num_bands"},
+                            {"alias": "num_channels"},
-                    ]
+                            {"alias": "num_bands"},
+                        ]
+                    }
                 }
-            }
+            },
-        },
+        )
     )
 
 
@@ -518,9 +602,6 @@ class DecompositionSeriesBands(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class Units(DynamicTable):
@@ -533,9 +614,18 @@ class Units(DynamicTable):
     )
 
     name: str = Field("Units", json_schema_extra={"linkml_meta": {"ifabsent": "string(Units)"}})
-    spike_times_index: Optional[Named[VectorIndex]] = Field(
+    electrode_group: Optional[VectorData[NDArray[Any, ElectrodeGroup]]] = Field(
         None,
-        description="""Index into the spike_times dataset.""",
+        description="""Electrode group that each spike unit came from.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
+    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+        None,
+        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -545,12 +635,9 @@ class Units(DynamicTable):
             }
         },
     )
-    spike_times: Optional[UnitsSpikeTimes] = Field(
+    electrodes_index: Optional[Named[VectorIndex]] = Field(
-        None, description="""Spike times for each unit."""
-    )
-    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into the obs_intervals dataset.""",
+        description="""Index into electrodes.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -576,9 +663,9 @@ class Units(DynamicTable):
             },
         )
     )
-    electrodes_index: Optional[Named[VectorIndex]] = Field(
+    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into electrodes.""",
+        description="""Index into the obs_intervals dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -588,9 +675,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+    spike_times: Optional[UnitsSpikeTimes] = Field(
+        None, description="""Spike times for each unit."""
+    )
+    spike_times_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
+        description="""Index into the spike_times dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -600,25 +690,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
+    waveform_mean: Optional[UnitsWaveformMean] = Field(
-        None, description="""Electrode group that each spike unit came from."""
+        None, description="""Spike waveform mean for each spike unit."""
+    )
+    waveform_sd: Optional[UnitsWaveformSd] = Field(
+        None, description="""Spike waveform standard deviation for each spike unit."""
     )
-    waveform_mean: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -629,9 +706,6 @@ class Units(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class UnitsSpikeTimes(VectorData):
@@ -654,14 +728,62 @@ class UnitsSpikeTimes(VectorData):
     description: str = Field(..., description="""Description of what these vectors represent.""")
 
 
+class UnitsWaveformMean(VectorData):
+    """
+    Spike waveform mean for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_mean"] = Field(
+        "waveform_mean",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_mean", "ifabsent": "string(waveform_mean)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+
+
+class UnitsWaveformSd(VectorData):
+    """
+    Spike waveform standard deviation for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_sd"] = Field(
+        "waveform_sd",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_sd", "ifabsent": "string(waveform_sd)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 AbstractFeatureSeries.model_rebuild()
 AbstractFeatureSeriesData.model_rebuild()
 AnnotationSeries.model_rebuild()
+AnnotationSeriesData.model_rebuild()
 IntervalSeries.model_rebuild()
+IntervalSeriesData.model_rebuild()
 DecompositionSeries.model_rebuild()
 DecompositionSeriesData.model_rebuild()
 DecompositionSeriesBands.model_rebuild()
 Units.model_rebuild()
 UnitsSpikeTimes.model_rebuild()
+UnitsWaveformMean.model_rebuild()
+UnitsWaveformSd.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_ogen.py

@@ -158,10 +158,8 @@ class OptogeneticSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], float] = Field(
+    data: OptogeneticSeriesData = Field(
-        ...,
+        ..., description="""Applied power for optogenetic stimulus, in watts."""
-        description="""Applied power for optogenetic stimulus, in watts.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     site: Union[OptogeneticStimulusSite, str] = Field(
         ...,
@@ -209,6 +207,37 @@ class OptogeneticSeries(TimeSeries):
     )
 
 
+class OptogeneticSeriesData(ConfiguredBaseModel):
+    """
+    Applied power for optogenetic stimulus, in watts.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ogen"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["watts"] = Field(
+        "watts",
+        description="""Unit of measurement for data, which is fixed to 'watts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "watts", "ifabsent": "string(watts)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class OptogeneticStimulusSite(NWBContainer):
     """
     A site of optogenetic stimulation.
@@ -239,4 +268,5 @@ class OptogeneticStimulusSite(NWBContainer):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 OptogeneticSeries.model_rebuild()
+OptogeneticSeriesData.model_rebuild()
 OptogeneticStimulusSite.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_ophys.py

@@ -28,7 +28,7 @@ from ...core.v2_2_0.core_nwb_base import (
     TimeSeriesSync,
 )
 from ...core.v2_2_0.core_nwb_device import Device
-from ...core.v2_2_0.core_nwb_image import ImageSeries, ImageSeriesExternalFile
+from ...core.v2_2_0.core_nwb_image import ImageSeries, ImageSeriesData, ImageSeriesExternalFile
 from ...hdmf_common.v1_1_0.hdmf_common_table import DynamicTable, DynamicTableRegion
 
 
@@ -209,12 +209,9 @@ class TwoPhotonSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -225,8 +222,9 @@ class TwoPhotonSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -275,9 +273,7 @@ class RoiResponseSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: RoiResponseSeriesData = Field(..., description="""Signals from ROIs.""")
-        NDArray[Shape["* num_times"], float], NDArray[Shape["* num_times, * num_rois"], float]
-    ] = Field(..., description="""Signals from ROIs.""")
     rois: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.""",
@@ -327,6 +323,39 @@ class RoiResponseSeries(TimeSeries):
     )
 
 
+class RoiResponseSeriesData(ConfiguredBaseModel):
+    """
+    Signals from ROIs.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_rois"], float | int],
+        ]
+    ] = Field(None)
+
+
 class DfOverF(NWBDataInterface):
     """
     dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).
@@ -336,10 +365,10 @@ class DfOverF(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field("DfOverF", json_schema_extra={"linkml_meta": {"ifabsent": "string(DfOverF)"}})
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Fluorescence(NWBDataInterface):
@@ -351,10 +380,12 @@ class Fluorescence(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field(
+        "Fluorescence", json_schema_extra={"linkml_meta": {"ifabsent": "string(Fluorescence)"}}
+    )
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ImageSegmentation(NWBDataInterface):
@@ -366,10 +397,13 @@ class ImageSegmentation(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[DynamicTable]] = Field(
+    name: str = Field(
+        "ImageSegmentation",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(ImageSegmentation)"}},
+    )
+    value: Optional[Dict[str, DynamicTable]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "DynamicTable"}]}}
     )
-    name: str = Field(...)
 
 
 class ImagingPlane(NWBContainer):
@@ -538,16 +572,20 @@ class MotionCorrection(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[NWBDataInterface]] = Field(
+    name: str = Field(
+        "MotionCorrection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(MotionCorrection)"}},
+    )
+    value: Optional[Dict[str, NWBDataInterface]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "NWBDataInterface"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 TwoPhotonSeries.model_rebuild()
 RoiResponseSeries.model_rebuild()
+RoiResponseSeriesData.model_rebuild()
 DfOverF.model_rebuild()
 Fluorescence.model_rebuild()
 ImageSegmentation.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/core_nwb_retinotopy.py

@@ -235,7 +235,7 @@ class RetinotopyImage(GrayscaleImage):
     )
     field_of_view: List[float] = Field(..., description="""Size of viewing area, in meters.""")
     format: str = Field(..., description="""Format of image. Right now only 'raw' is supported.""")
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -374,7 +374,7 @@ class ImagingRetinotopyFocalDepthImage(RetinotopyImage):
     )
     field_of_view: List[float] = Field(..., description="""Size of viewing area, in meters.""")
     format: str = Field(..., description="""Format of image. Right now only 'raw' is supported.""")
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}

nwb_models/src/nwb_models/models/pydantic/core/v2_2_0/namespace.py

@@ -38,6 +38,7 @@ from ...core.v2_2_0.core_nwb_ecephys import (
     ClusterWaveforms,
     Clustering,
     ElectricalSeries,
+    ElectricalSeriesData,
     ElectrodeGroup,
     ElectrodeGroupPosition,
     EventDetection,
@@ -46,6 +47,7 @@ from ...core.v2_2_0.core_nwb_ecephys import (
     FilteredEphys,
     LFP,
     SpikeEventSeries,
+    SpikeEventSeriesData,
 )
 from ...core.v2_2_0.core_nwb_epoch import TimeIntervals, TimeIntervalsTimeseries
 from ...core.v2_2_0.core_nwb_file import (
@@ -85,8 +87,10 @@ from ...core.v2_2_0.core_nwb_image import (
     GrayscaleImage,
     ImageMaskSeries,
     ImageSeries,
+    ImageSeriesData,
     ImageSeriesExternalFile,
     IndexSeries,
+    IndexSeriesData,
     OpticalSeries,
     RGBAImage,
     RGBImage,
@@ -95,14 +99,22 @@ from ...core.v2_2_0.core_nwb_misc import (
     AbstractFeatureSeries,
     AbstractFeatureSeriesData,
     AnnotationSeries,
+    AnnotationSeriesData,
     DecompositionSeries,
     DecompositionSeriesBands,
     DecompositionSeriesData,
     IntervalSeries,
+    IntervalSeriesData,
     Units,
     UnitsSpikeTimes,
+    UnitsWaveformMean,
+    UnitsWaveformSd,
+)
+from ...core.v2_2_0.core_nwb_ogen import (
+    OptogeneticSeries,
+    OptogeneticSeriesData,
+    OptogeneticStimulusSite,
 )
-from ...core.v2_2_0.core_nwb_ogen import OptogeneticSeries, OptogeneticStimulusSite
 from ...core.v2_2_0.core_nwb_ophys import (
     DfOverF,
     Fluorescence,
@@ -114,6 +126,7 @@ from ...core.v2_2_0.core_nwb_ophys import (
     MotionCorrection,
     OpticalChannel,
     RoiResponseSeries,
+    RoiResponseSeriesData,
     TwoPhotonSeries,
 )
 from ...core.v2_2_0.core_nwb_retinotopy import (

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_base.py

@@ -170,9 +170,9 @@ class Image(NWBData):
     description: Optional[str] = Field(None, description="""Description of the image.""")
     value: Optional[
         Union[
-            NDArray[Shape["* x, * y"], float],
+            NDArray[Shape["* x, * y"], float | int],
-            NDArray[Shape["* x, * y, 3 r_g_b"], float],
+            NDArray[Shape["* x, * y, 3 r_g_b"], float | int],
-            NDArray[Shape["* x, * y, 4 r_g_b_a"], float],
+            NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int],
         ]
     ] = Field(None)
 
@@ -333,13 +333,16 @@ class ProcessingModule(NWBContainer):
         {"from_schema": "core.nwb.base", "tree_root": True}
     )
 
-    value: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    name: str = Field(...)
+    description: str = Field(
+        ..., description="""Description of this collection of processed data."""
+    )
+    value: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    name: str = Field(...)
 
 
 class Images(NWBDataInterface):
@@ -353,7 +356,7 @@ class Images(NWBDataInterface):
 
     name: str = Field("Images", json_schema_extra={"linkml_meta": {"ifabsent": "string(Images)"}})
     description: str = Field(..., description="""Description of this collection of images.""")
-    image: List[Image] = Field(..., description="""Images stored in this collection.""")
+    image: List[str] = Field(..., description="""Images stored in this collection.""")
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_behavior.py

@@ -213,6 +213,16 @@ class SpatialSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "meters",
         description="""Base unit of measurement for working with the data. The default value is 'meters'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -220,8 +230,8 @@ class SpatialSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -235,10 +245,13 @@ class BehavioralEpochs(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[IntervalSeries]] = Field(
+    name: str = Field(
+        "BehavioralEpochs",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEpochs)"}},
+    )
+    value: Optional[Dict[str, IntervalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "IntervalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralEvents(NWBDataInterface):
@@ -250,10 +263,13 @@ class BehavioralEvents(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralEvents",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEvents)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralTimeSeries(NWBDataInterface):
@@ -265,10 +281,13 @@ class BehavioralTimeSeries(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralTimeSeries",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralTimeSeries)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class PupilTracking(NWBDataInterface):
@@ -280,10 +299,12 @@ class PupilTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "PupilTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(PupilTracking)"}}
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class EyeTracking(NWBDataInterface):
@@ -295,10 +316,12 @@ class EyeTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "EyeTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(EyeTracking)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class CompassDirection(NWBDataInterface):
@@ -310,10 +333,13 @@ class CompassDirection(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "CompassDirection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(CompassDirection)"}},
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Position(NWBDataInterface):
@@ -325,10 +351,12 @@ class Position(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "Position", json_schema_extra={"linkml_meta": {"ifabsent": "string(Position)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_ecephys.py

@@ -190,11 +190,12 @@ class ElectricalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        NDArray[Shape["* num_times"], float],
+        None,
-        NDArray[Shape["* num_times, * num_channels"], float],
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        NDArray[Shape["* num_times, * num_channels, * num_samples"], float],
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    ] = Field(..., description="""Recorded voltage data.""")
+    )
+    data: ElectricalSeriesData = Field(..., description="""Recorded voltage data.""")
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -207,11 +208,6 @@ class ElectricalSeries(TimeSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -249,6 +245,41 @@ class ElectricalSeries(TimeSeries):
     )
 
 
+class ElectricalSeriesData(ConfiguredBaseModel):
+    """
+    Recorded voltage data.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Base unit of measurement for working with the data. This value is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and 'channel_conversion' (if present).""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_channels"], float | int],
+            NDArray[Shape["* num_times, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class SpikeEventSeries(ElectricalSeries):
     """
     Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).
@@ -259,15 +290,17 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: SpikeEventSeriesData = Field(..., description="""Spike waveforms.""")
-        NDArray[Shape["* num_events, * num_samples"], float],
-        NDArray[Shape["* num_events, * num_channels, * num_samples"], float],
-    ] = Field(..., description="""Spike waveforms.""")
     timestamps: NDArray[Shape["* num_times"], float] = Field(
         ...,
         description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
+        None,
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
+    )
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -280,11 +313,6 @@ class SpikeEventSeries(ElectricalSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -317,6 +345,40 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
 
+class SpikeEventSeriesData(ConfiguredBaseModel):
+    """
+    Spike waveforms.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Unit of measurement for waveforms, which is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_events, * num_samples"], float | int],
+            NDArray[Shape["* num_events, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class FeatureExtraction(NWBDataInterface):
     """
     Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.
@@ -415,10 +477,12 @@ class EventWaveform(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[SpikeEventSeries]] = Field(
+    name: str = Field(
+        "EventWaveform", json_schema_extra={"linkml_meta": {"ifabsent": "string(EventWaveform)"}}
+    )
+    value: Optional[Dict[str, SpikeEventSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpikeEventSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class FilteredEphys(NWBDataInterface):
@@ -430,10 +494,12 @@ class FilteredEphys(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field(
+        "FilteredEphys", json_schema_extra={"linkml_meta": {"ifabsent": "string(FilteredEphys)"}}
+    )
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class LFP(NWBDataInterface):
@@ -445,10 +511,10 @@ class LFP(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field("LFP", json_schema_extra={"linkml_meta": {"ifabsent": "string(LFP)"}})
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ElectrodeGroup(NWBContainer):
@@ -591,7 +657,9 @@ class Clustering(NWBDataInterface):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 ElectricalSeries.model_rebuild()
+ElectricalSeriesData.model_rebuild()
 SpikeEventSeries.model_rebuild()
+SpikeEventSeriesData.model_rebuild()
 FeatureExtraction.model_rebuild()
 EventDetection.model_rebuild()
 EventWaveform.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_epoch.py

@@ -247,9 +247,6 @@ class TimeIntervals(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class TimeIntervalsTimeseries(VectorData):

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_file.py

@@ -211,28 +211,28 @@ class NWBFile(NWBContainer):
         ...,
         description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""",
     )
-    acquisition: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    acquisition: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    analysis: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    analysis: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    scratch: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    scratch: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    processing: Optional[List[ProcessingModule]] = Field(
+    processing: Optional[Dict[str, ProcessingModule]] = Field(
         None,
         description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ProcessingModule"}]}},
@@ -250,6 +250,9 @@ class NWBFile(NWBContainer):
         description="""Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.""",
     )
     units: Optional[Units] = Field(None, description="""Data about sorted spike units.""")
+    specifications: Optional[dict] = Field(
+        None, description="""Nested dictionary of schema specifications"""
+    )
 
 
 class NWBFileStimulus(ConfiguredBaseModel):
@@ -265,12 +268,12 @@ class NWBFileStimulus(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "stimulus", "ifabsent": "string(stimulus)"}
         },
     )
-    presentation: Optional[List[TimeSeries]] = Field(
+    presentation: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Stimuli presented during the experiment.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
     )
-    templates: Optional[List[TimeSeries]] = Field(
+    templates: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
@@ -348,11 +351,11 @@ class NWBFileGeneral(ConfiguredBaseModel):
         None,
         description="""Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc.""",
     )
-    nwb_container: Optional[List[NWBContainer]] = Field(
+    nwb_container: Optional[Dict[str, NWBContainer]] = Field(
         None,
         description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
     )
-    devices: Optional[List[Device]] = Field(
+    devices: Optional[Dict[str, Device]] = Field(
         None,
         description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "Device"}]}},
@@ -367,12 +370,12 @@ class NWBFileGeneral(ConfiguredBaseModel):
     intracellular_ephys: Optional[GeneralIntracellularEphys] = Field(
         None, description="""Metadata related to intracellular electrophysiology."""
     )
-    optogenetics: Optional[List[OptogeneticStimulusSite]] = Field(
+    optogenetics: Optional[Dict[str, OptogeneticStimulusSite]] = Field(
         None,
         description="""Metadata describing optogenetic stimuluation.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "OptogeneticStimulusSite"}]}},
     )
-    optophysiology: Optional[List[ImagingPlane]] = Field(
+    optophysiology: Optional[Dict[str, ImagingPlane]] = Field(
         None,
         description="""Metadata related to optophysiology.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImagingPlane"}]}},
@@ -450,12 +453,12 @@ class GeneralExtracellularEphys(ConfiguredBaseModel):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
-        None, description="""Physical group of electrodes."""
-    )
     electrodes: Optional[ExtracellularEphysElectrodes] = Field(
         None, description="""A table of all electrodes (i.e. channels) used for recording."""
     )
+    value: Optional[Dict[str, ElectrodeGroup]] = Field(
+        None, description="""Physical group of electrodes."""
+    )
 
 
 class ExtracellularEphysElectrodes(DynamicTable):
@@ -525,8 +528,14 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    group: List[ElectrodeGroup] = Field(
+    group: VectorData[NDArray[Any, ElectrodeGroup]] = Field(
-        ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
+        ...,
+        description="""Reference to the ElectrodeGroup this electrode is a part of.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
     )
     group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
@@ -583,9 +592,6 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class GeneralIntracellularEphys(ConfiguredBaseModel):
@@ -608,12 +614,12 @@ class GeneralIntracellularEphys(ConfiguredBaseModel):
         None,
         description="""Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries.""",
     )
-    intracellular_electrode: Optional[List[IntracellularElectrode]] = Field(
-        None, description="""An intracellular electrode."""
-    )
     sweep_table: Optional[SweepTable] = Field(
         None, description="""The table which groups different PatchClampSeries together."""
     )
+    value: Optional[Dict[str, IntracellularElectrode]] = Field(
+        None, description="""An intracellular electrode."""
+    )
 
 
 class NWBFileIntervals(ConfiguredBaseModel):
@@ -639,7 +645,7 @@ class NWBFileIntervals(ConfiguredBaseModel):
     invalid_times: Optional[TimeIntervals] = Field(
         None, description="""Time intervals that should be removed from analysis."""
     )
-    time_intervals: Optional[List[TimeIntervals]] = Field(
+    value: Optional[Dict[str, TimeIntervals]] = Field(
         None,
         description="""Optional additional table(s) for describing other experimental time intervals.""",
     )

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_icephys.py

@@ -262,11 +262,21 @@ class PatchClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         ...,
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
     )
-    value: Optional[NDArray[Shape["* num_times"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
         None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
     )
 
@@ -281,12 +291,12 @@ class CurrentClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     bias_current: Optional[float] = Field(None, description="""Bias current, in amps.""")
     bridge_balance: Optional[float] = Field(None, description="""Bridge balance, in ohms.""")
     capacitance_compensation: Optional[float] = Field(
         None, description="""Capacitance compensation, in farads."""
     )
+    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     stimulus_description: str = Field(
         ..., description="""Protocol/stimulus name for this patch-clamp dataset."""
     )
@@ -354,12 +364,24 @@ class CurrentClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IZeroClampSeries(CurrentClampSeries):
@@ -512,6 +534,16 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["amperes"] = Field(
         "amperes",
         description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -519,7 +551,9 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
         },
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class VoltageClampSeries(PatchClampSeries):
@@ -532,13 +566,13 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     capacitance_fast: Optional[VoltageClampSeriesCapacitanceFast] = Field(
         None, description="""Fast capacitance, in farads."""
     )
     capacitance_slow: Optional[VoltageClampSeriesCapacitanceSlow] = Field(
         None, description="""Slow capacitance, in farads."""
     )
+    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     resistance_comp_bandwidth: Optional[VoltageClampSeriesResistanceCompBandwidth] = Field(
         None, description="""Resistance compensation bandwidth, in hertz."""
     )
@@ -610,27 +644,6 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
 
-class VoltageClampSeriesData(ConfiguredBaseModel):
-    """
-    Recorded current.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
-
-    name: Literal["data"] = Field(
-        "data",
-        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
-    )
-    unit: Literal["amperes"] = Field(
-        "amperes",
-        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
-        },
-    )
-    value: Any = Field(...)
-
-
 class VoltageClampSeriesCapacitanceFast(ConfiguredBaseModel):
     """
     Fast capacitance, in farads.
@@ -683,6 +696,39 @@ class VoltageClampSeriesCapacitanceSlow(ConfiguredBaseModel):
     value: float = Field(...)
 
 
+class VoltageClampSeriesData(ConfiguredBaseModel):
+    """
+    Recorded current.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["amperes"] = Field(
+        "amperes",
+        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
+        },
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class VoltageClampSeriesResistanceCompBandwidth(ConfiguredBaseModel):
     """
     Resistance compensation bandwidth, in hertz.
@@ -887,12 +933,24 @@ class VoltageClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IntracellularElectrode(NWBContainer):
@@ -942,18 +1000,15 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: VectorData[NDArray[Any, int]] = Field(
+    series: VectorData[NDArray[Any, PatchClampSeries]] = Field(
         ...,
-        description="""Sweep number of the PatchClampSeries in that row.""",
+        description="""The PatchClampSeries with the sweep number in that row.""",
         json_schema_extra={
             "linkml_meta": {
                 "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
             }
         },
     )
-    series: List[PatchClampSeries] = Field(
-        ..., description="""The PatchClampSeries with the sweep number in that row."""
-    )
     series_index: Named[VectorIndex] = Field(
         ...,
         description="""Index for series.""",
@@ -966,6 +1021,15 @@ class SweepTable(DynamicTable):
             }
         },
     )
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
+        ...,
+        description="""Sweep number of the PatchClampSeries in that row.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -976,9 +1040,6 @@ class SweepTable(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild
@@ -991,9 +1052,9 @@ IZeroClampSeries.model_rebuild()
 CurrentClampStimulusSeries.model_rebuild()
 CurrentClampStimulusSeriesData.model_rebuild()
 VoltageClampSeries.model_rebuild()
-VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesCapacitanceFast.model_rebuild()
 VoltageClampSeriesCapacitanceSlow.model_rebuild()
+VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesResistanceCompBandwidth.model_rebuild()
 VoltageClampSeriesResistanceCompCorrection.model_rebuild()
 VoltageClampSeriesResistanceCompPrediction.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_image.py

@@ -152,7 +152,7 @@ class GrayscaleImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -174,7 +174,7 @@ class RGBImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -204,7 +204,7 @@ class RGBAImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -234,12 +234,9 @@ class ImageSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -250,8 +247,9 @@ class ImageSeries(TimeSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -290,6 +288,39 @@ class ImageSeries(TimeSeries):
     )
 
 
+class ImageSeriesData(ConfiguredBaseModel):
+    """
+    Binary data representing images across frames.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, * z"], float | int],
+        ]
+    ] = Field(None)
+
+
 class ImageSeriesExternalFile(ConfiguredBaseModel):
     """
     Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.
@@ -331,12 +362,9 @@ class ImageMaskSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -347,8 +375,9 @@ class ImageMaskSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -409,12 +438,9 @@ class OpticalSeries(ImageSeries):
         None,
         description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""",
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -425,8 +451,9 @@ class OpticalSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -475,10 +502,8 @@ class IndexSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IndexSeriesData = Field(
-        ...,
+        ..., description="""Index of the frame in the referenced ImageSeries."""
-        description="""Index of the frame in the referenced ImageSeries.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     indexed_timeseries: Union[ImageSeries, str] = Field(
         ...,
@@ -526,13 +551,45 @@ class IndexSeries(TimeSeries):
     )
 
 
+class IndexSeriesData(ConfiguredBaseModel):
+    """
+    Index of the frame in the referenced ImageSeries.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 GrayscaleImage.model_rebuild()
 RGBImage.model_rebuild()
 RGBAImage.model_rebuild()
 ImageSeries.model_rebuild()
+ImageSeriesData.model_rebuild()
 ImageSeriesExternalFile.model_rebuild()
 ImageMaskSeries.model_rebuild()
 OpticalSeries.model_rebuild()
 IndexSeries.model_rebuild()
+IndexSeriesData.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_misc.py

@@ -251,6 +251,16 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "see ",
         description="""Since there can be different units for different features, store the units in 'feature_units'. The default value for this attribute is \"see 'feature_units'\".""",
@@ -258,8 +268,8 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -274,10 +284,8 @@ class AnnotationSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], str] = Field(
+    data: AnnotationSeriesData = Field(
-        ...,
+        ..., description="""Annotations made during an experiment."""
-        description="""Annotations made during an experiment.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -316,6 +324,39 @@ class AnnotationSeries(TimeSeries):
     )
 
 
+class AnnotationSeriesData(ConfiguredBaseModel):
+    """
+    Annotations made during an experiment.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], str]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class IntervalSeries(TimeSeries):
     """
     Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.
@@ -326,10 +367,8 @@ class IntervalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IntervalSeriesData = Field(
-        ...,
+        ..., description="""Use values >0 if interval started, <0 if interval ended."""
-        description="""Use values >0 if interval started, <0 if interval ended.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -368,6 +407,39 @@ class IntervalSeries(TimeSeries):
     )
 
 
+class IntervalSeriesData(ConfiguredBaseModel):
+    """
+    Use values >0 if interval started, <0 if interval ended.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class DecompositionSeries(TimeSeries):
     """
     Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -443,24 +515,36 @@ class DecompositionSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         "no unit",
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"ifabsent": "string(no unit)"}},
     )
-    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float | int]] = (
-        None,
+        Field(
-        json_schema_extra={
+            None,
-            "linkml_meta": {
+            json_schema_extra={
-                "array": {
+                "linkml_meta": {
-                    "dimensions": [
+                    "array": {
-                        {"alias": "num_times"},
+                        "dimensions": [
-                        {"alias": "num_channels"},
+                            {"alias": "num_times"},
-                        {"alias": "num_bands"},
+                            {"alias": "num_channels"},
-                    ]
+                            {"alias": "num_bands"},
+                        ]
+                    }
                 }
-            }
+            },
-        },
+        )
     )
 
 
@@ -518,9 +602,6 @@ class DecompositionSeriesBands(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class Units(DynamicTable):
@@ -533,9 +614,18 @@ class Units(DynamicTable):
     )
 
     name: str = Field("Units", json_schema_extra={"linkml_meta": {"ifabsent": "string(Units)"}})
-    spike_times_index: Optional[Named[VectorIndex]] = Field(
+    electrode_group: Optional[VectorData[NDArray[Any, ElectrodeGroup]]] = Field(
         None,
-        description="""Index into the spike_times dataset.""",
+        description="""Electrode group that each spike unit came from.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
+    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+        None,
+        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -545,12 +635,9 @@ class Units(DynamicTable):
             }
         },
     )
-    spike_times: Optional[UnitsSpikeTimes] = Field(
+    electrodes_index: Optional[Named[VectorIndex]] = Field(
-        None, description="""Spike times for each unit."""
-    )
-    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into the obs_intervals dataset.""",
+        description="""Index into electrodes.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -576,9 +663,9 @@ class Units(DynamicTable):
             },
         )
     )
-    electrodes_index: Optional[Named[VectorIndex]] = Field(
+    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into electrodes.""",
+        description="""Index into the obs_intervals dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -588,9 +675,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+    spike_times: Optional[UnitsSpikeTimes] = Field(
+        None, description="""Spike times for each unit."""
+    )
+    spike_times_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
+        description="""Index into the spike_times dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -600,25 +690,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
+    waveform_mean: Optional[UnitsWaveformMean] = Field(
-        None, description="""Electrode group that each spike unit came from."""
+        None, description="""Spike waveform mean for each spike unit."""
+    )
+    waveform_sd: Optional[UnitsWaveformSd] = Field(
+        None, description="""Spike waveform standard deviation for each spike unit."""
     )
-    waveform_mean: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -629,9 +706,6 @@ class Units(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class UnitsSpikeTimes(VectorData):
@@ -654,14 +728,62 @@ class UnitsSpikeTimes(VectorData):
     description: str = Field(..., description="""Description of what these vectors represent.""")
 
 
+class UnitsWaveformMean(VectorData):
+    """
+    Spike waveform mean for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_mean"] = Field(
+        "waveform_mean",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_mean", "ifabsent": "string(waveform_mean)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+
+
+class UnitsWaveformSd(VectorData):
+    """
+    Spike waveform standard deviation for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_sd"] = Field(
+        "waveform_sd",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_sd", "ifabsent": "string(waveform_sd)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 AbstractFeatureSeries.model_rebuild()
 AbstractFeatureSeriesData.model_rebuild()
 AnnotationSeries.model_rebuild()
+AnnotationSeriesData.model_rebuild()
 IntervalSeries.model_rebuild()
+IntervalSeriesData.model_rebuild()
 DecompositionSeries.model_rebuild()
 DecompositionSeriesData.model_rebuild()
 DecompositionSeriesBands.model_rebuild()
 Units.model_rebuild()
 UnitsSpikeTimes.model_rebuild()
+UnitsWaveformMean.model_rebuild()
+UnitsWaveformSd.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_ogen.py

@@ -158,10 +158,8 @@ class OptogeneticSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], float] = Field(
+    data: OptogeneticSeriesData = Field(
-        ...,
+        ..., description="""Applied power for optogenetic stimulus, in watts."""
-        description="""Applied power for optogenetic stimulus, in watts.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     site: Union[OptogeneticStimulusSite, str] = Field(
         ...,
@@ -209,6 +207,37 @@ class OptogeneticSeries(TimeSeries):
     )
 
 
+class OptogeneticSeriesData(ConfiguredBaseModel):
+    """
+    Applied power for optogenetic stimulus, in watts.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ogen"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["watts"] = Field(
+        "watts",
+        description="""Unit of measurement for data, which is fixed to 'watts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "watts", "ifabsent": "string(watts)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class OptogeneticStimulusSite(NWBContainer):
     """
     A site of optogenetic stimulation.
@@ -239,4 +268,5 @@ class OptogeneticStimulusSite(NWBContainer):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 OptogeneticSeries.model_rebuild()
+OptogeneticSeriesData.model_rebuild()
 OptogeneticStimulusSite.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_ophys.py

@@ -28,7 +28,7 @@ from ...core.v2_2_1.core_nwb_base import (
     TimeSeriesSync,
 )
 from ...core.v2_2_1.core_nwb_device import Device
-from ...core.v2_2_1.core_nwb_image import ImageSeries, ImageSeriesExternalFile
+from ...core.v2_2_1.core_nwb_image import ImageSeries, ImageSeriesData, ImageSeriesExternalFile
 from ...hdmf_common.v1_1_2.hdmf_common_table import DynamicTable, DynamicTableRegion
 
 
@@ -209,12 +209,9 @@ class TwoPhotonSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -225,8 +222,9 @@ class TwoPhotonSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -275,9 +273,7 @@ class RoiResponseSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: RoiResponseSeriesData = Field(..., description="""Signals from ROIs.""")
-        NDArray[Shape["* num_times"], float], NDArray[Shape["* num_times, * num_rois"], float]
-    ] = Field(..., description="""Signals from ROIs.""")
     rois: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.""",
@@ -327,6 +323,39 @@ class RoiResponseSeries(TimeSeries):
     )
 
 
+class RoiResponseSeriesData(ConfiguredBaseModel):
+    """
+    Signals from ROIs.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_rois"], float | int],
+        ]
+    ] = Field(None)
+
+
 class DfOverF(NWBDataInterface):
     """
     dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).
@@ -336,10 +365,10 @@ class DfOverF(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field("DfOverF", json_schema_extra={"linkml_meta": {"ifabsent": "string(DfOverF)"}})
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Fluorescence(NWBDataInterface):
@@ -351,10 +380,12 @@ class Fluorescence(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field(
+        "Fluorescence", json_schema_extra={"linkml_meta": {"ifabsent": "string(Fluorescence)"}}
+    )
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ImageSegmentation(NWBDataInterface):
@@ -366,10 +397,13 @@ class ImageSegmentation(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[DynamicTable]] = Field(
+    name: str = Field(
+        "ImageSegmentation",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(ImageSegmentation)"}},
+    )
+    value: Optional[Dict[str, DynamicTable]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "DynamicTable"}]}}
     )
-    name: str = Field(...)
 
 
 class ImagingPlane(NWBContainer):
@@ -538,16 +572,20 @@ class MotionCorrection(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[NWBDataInterface]] = Field(
+    name: str = Field(
+        "MotionCorrection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(MotionCorrection)"}},
+    )
+    value: Optional[Dict[str, NWBDataInterface]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "NWBDataInterface"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 TwoPhotonSeries.model_rebuild()
 RoiResponseSeries.model_rebuild()
+RoiResponseSeriesData.model_rebuild()
 DfOverF.model_rebuild()
 Fluorescence.model_rebuild()
 ImageSegmentation.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/core_nwb_retinotopy.py

@@ -235,7 +235,7 @@ class RetinotopyImage(GrayscaleImage):
     )
     field_of_view: List[float] = Field(..., description="""Size of viewing area, in meters.""")
     format: str = Field(..., description="""Format of image. Right now only 'raw' is supported.""")
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -374,7 +374,7 @@ class ImagingRetinotopyFocalDepthImage(RetinotopyImage):
     )
     field_of_view: List[float] = Field(..., description="""Size of viewing area, in meters.""")
     format: str = Field(..., description="""Format of image. Right now only 'raw' is supported.""")
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}

nwb_models/src/nwb_models/models/pydantic/core/v2_2_1/namespace.py

@@ -38,6 +38,7 @@ from ...core.v2_2_1.core_nwb_ecephys import (
     ClusterWaveforms,
     Clustering,
     ElectricalSeries,
+    ElectricalSeriesData,
     ElectrodeGroup,
     ElectrodeGroupPosition,
     EventDetection,
@@ -46,6 +47,7 @@ from ...core.v2_2_1.core_nwb_ecephys import (
     FilteredEphys,
     LFP,
     SpikeEventSeries,
+    SpikeEventSeriesData,
 )
 from ...core.v2_2_1.core_nwb_epoch import TimeIntervals, TimeIntervalsTimeseries
 from ...core.v2_2_1.core_nwb_file import (
@@ -85,8 +87,10 @@ from ...core.v2_2_1.core_nwb_image import (
     GrayscaleImage,
     ImageMaskSeries,
     ImageSeries,
+    ImageSeriesData,
     ImageSeriesExternalFile,
     IndexSeries,
+    IndexSeriesData,
     OpticalSeries,
     RGBAImage,
     RGBImage,
@@ -95,14 +99,22 @@ from ...core.v2_2_1.core_nwb_misc import (
     AbstractFeatureSeries,
     AbstractFeatureSeriesData,
     AnnotationSeries,
+    AnnotationSeriesData,
     DecompositionSeries,
     DecompositionSeriesBands,
     DecompositionSeriesData,
     IntervalSeries,
+    IntervalSeriesData,
     Units,
     UnitsSpikeTimes,
+    UnitsWaveformMean,
+    UnitsWaveformSd,
+)
+from ...core.v2_2_1.core_nwb_ogen import (
+    OptogeneticSeries,
+    OptogeneticSeriesData,
+    OptogeneticStimulusSite,
 )
-from ...core.v2_2_1.core_nwb_ogen import OptogeneticSeries, OptogeneticStimulusSite
 from ...core.v2_2_1.core_nwb_ophys import (
     DfOverF,
     Fluorescence,
@@ -114,6 +126,7 @@ from ...core.v2_2_1.core_nwb_ophys import (
     MotionCorrection,
     OpticalChannel,
     RoiResponseSeries,
+    RoiResponseSeriesData,
     TwoPhotonSeries,
 )
 from ...core.v2_2_1.core_nwb_retinotopy import (

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_base.py

@@ -170,9 +170,9 @@ class Image(NWBData):
     description: Optional[str] = Field(None, description="""Description of the image.""")
     value: Optional[
         Union[
-            NDArray[Shape["* x, * y"], float],
+            NDArray[Shape["* x, * y"], float | int],
-            NDArray[Shape["* x, * y, 3 r_g_b"], float],
+            NDArray[Shape["* x, * y, 3 r_g_b"], float | int],
-            NDArray[Shape["* x, * y, 4 r_g_b_a"], float],
+            NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int],
         ]
     ] = Field(None)
 
@@ -333,13 +333,16 @@ class ProcessingModule(NWBContainer):
         {"from_schema": "core.nwb.base", "tree_root": True}
     )
 
-    value: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    name: str = Field(...)
+    description: str = Field(
+        ..., description="""Description of this collection of processed data."""
+    )
+    value: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    name: str = Field(...)
 
 
 class Images(NWBDataInterface):
@@ -353,7 +356,7 @@ class Images(NWBDataInterface):
 
     name: str = Field("Images", json_schema_extra={"linkml_meta": {"ifabsent": "string(Images)"}})
     description: str = Field(..., description="""Description of this collection of images.""")
-    image: List[Image] = Field(..., description="""Images stored in this collection.""")
+    image: List[str] = Field(..., description="""Images stored in this collection.""")
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_behavior.py

@@ -213,6 +213,16 @@ class SpatialSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "meters",
         description="""Base unit of measurement for working with the data. The default value is 'meters'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -220,8 +230,8 @@ class SpatialSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -235,10 +245,13 @@ class BehavioralEpochs(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[IntervalSeries]] = Field(
+    name: str = Field(
+        "BehavioralEpochs",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEpochs)"}},
+    )
+    value: Optional[Dict[str, IntervalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "IntervalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralEvents(NWBDataInterface):
@@ -250,10 +263,13 @@ class BehavioralEvents(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralEvents",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEvents)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralTimeSeries(NWBDataInterface):
@@ -265,10 +281,13 @@ class BehavioralTimeSeries(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralTimeSeries",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralTimeSeries)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class PupilTracking(NWBDataInterface):
@@ -280,10 +299,12 @@ class PupilTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "PupilTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(PupilTracking)"}}
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class EyeTracking(NWBDataInterface):
@@ -295,10 +316,12 @@ class EyeTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "EyeTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(EyeTracking)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class CompassDirection(NWBDataInterface):
@@ -310,10 +333,13 @@ class CompassDirection(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "CompassDirection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(CompassDirection)"}},
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Position(NWBDataInterface):
@@ -325,10 +351,12 @@ class Position(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "Position", json_schema_extra={"linkml_meta": {"ifabsent": "string(Position)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_ecephys.py

@@ -190,11 +190,12 @@ class ElectricalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        NDArray[Shape["* num_times"], float],
+        None,
-        NDArray[Shape["* num_times, * num_channels"], float],
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        NDArray[Shape["* num_times, * num_channels, * num_samples"], float],
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    ] = Field(..., description="""Recorded voltage data.""")
+    )
+    data: ElectricalSeriesData = Field(..., description="""Recorded voltage data.""")
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -207,11 +208,6 @@ class ElectricalSeries(TimeSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -249,6 +245,41 @@ class ElectricalSeries(TimeSeries):
     )
 
 
+class ElectricalSeriesData(ConfiguredBaseModel):
+    """
+    Recorded voltage data.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Base unit of measurement for working with the data. This value is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and 'channel_conversion' (if present).""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_channels"], float | int],
+            NDArray[Shape["* num_times, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class SpikeEventSeries(ElectricalSeries):
     """
     Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).
@@ -259,15 +290,17 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: SpikeEventSeriesData = Field(..., description="""Spike waveforms.""")
-        NDArray[Shape["* num_events, * num_samples"], float],
-        NDArray[Shape["* num_events, * num_channels, * num_samples"], float],
-    ] = Field(..., description="""Spike waveforms.""")
     timestamps: NDArray[Shape["* num_times"], float] = Field(
         ...,
         description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
+        None,
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
+    )
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -280,11 +313,6 @@ class SpikeEventSeries(ElectricalSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -317,6 +345,40 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
 
+class SpikeEventSeriesData(ConfiguredBaseModel):
+    """
+    Spike waveforms.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Unit of measurement for waveforms, which is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_events, * num_samples"], float | int],
+            NDArray[Shape["* num_events, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class FeatureExtraction(NWBDataInterface):
     """
     Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.
@@ -415,10 +477,12 @@ class EventWaveform(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[SpikeEventSeries]] = Field(
+    name: str = Field(
+        "EventWaveform", json_schema_extra={"linkml_meta": {"ifabsent": "string(EventWaveform)"}}
+    )
+    value: Optional[Dict[str, SpikeEventSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpikeEventSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class FilteredEphys(NWBDataInterface):
@@ -430,10 +494,12 @@ class FilteredEphys(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field(
+        "FilteredEphys", json_schema_extra={"linkml_meta": {"ifabsent": "string(FilteredEphys)"}}
+    )
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class LFP(NWBDataInterface):
@@ -445,10 +511,10 @@ class LFP(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field("LFP", json_schema_extra={"linkml_meta": {"ifabsent": "string(LFP)"}})
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ElectrodeGroup(NWBContainer):
@@ -591,7 +657,9 @@ class Clustering(NWBDataInterface):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 ElectricalSeries.model_rebuild()
+ElectricalSeriesData.model_rebuild()
 SpikeEventSeries.model_rebuild()
+SpikeEventSeriesData.model_rebuild()
 FeatureExtraction.model_rebuild()
 EventDetection.model_rebuild()
 EventWaveform.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_epoch.py

@@ -247,9 +247,6 @@ class TimeIntervals(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class TimeIntervalsTimeseries(VectorData):

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_file.py

@@ -211,28 +211,28 @@ class NWBFile(NWBContainer):
         ...,
         description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""",
     )
-    acquisition: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    acquisition: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    analysis: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    analysis: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    scratch: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    scratch: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    processing: Optional[List[ProcessingModule]] = Field(
+    processing: Optional[Dict[str, ProcessingModule]] = Field(
         None,
         description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ProcessingModule"}]}},
@@ -250,6 +250,9 @@ class NWBFile(NWBContainer):
         description="""Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.""",
     )
     units: Optional[Units] = Field(None, description="""Data about sorted spike units.""")
+    specifications: Optional[dict] = Field(
+        None, description="""Nested dictionary of schema specifications"""
+    )
 
 
 class NWBFileStimulus(ConfiguredBaseModel):
@@ -265,12 +268,12 @@ class NWBFileStimulus(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "stimulus", "ifabsent": "string(stimulus)"}
         },
     )
-    presentation: Optional[List[TimeSeries]] = Field(
+    presentation: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Stimuli presented during the experiment.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
     )
-    templates: Optional[List[TimeSeries]] = Field(
+    templates: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
@@ -348,11 +351,11 @@ class NWBFileGeneral(ConfiguredBaseModel):
         None,
         description="""Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc.""",
     )
-    nwb_container: Optional[List[NWBContainer]] = Field(
+    nwb_container: Optional[Dict[str, NWBContainer]] = Field(
         None,
         description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
     )
-    devices: Optional[List[Device]] = Field(
+    devices: Optional[Dict[str, Device]] = Field(
         None,
         description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "Device"}]}},
@@ -367,12 +370,12 @@ class NWBFileGeneral(ConfiguredBaseModel):
     intracellular_ephys: Optional[GeneralIntracellularEphys] = Field(
         None, description="""Metadata related to intracellular electrophysiology."""
     )
-    optogenetics: Optional[List[OptogeneticStimulusSite]] = Field(
+    optogenetics: Optional[Dict[str, OptogeneticStimulusSite]] = Field(
         None,
         description="""Metadata describing optogenetic stimuluation.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "OptogeneticStimulusSite"}]}},
     )
-    optophysiology: Optional[List[ImagingPlane]] = Field(
+    optophysiology: Optional[Dict[str, ImagingPlane]] = Field(
         None,
         description="""Metadata related to optophysiology.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImagingPlane"}]}},
@@ -450,12 +453,12 @@ class GeneralExtracellularEphys(ConfiguredBaseModel):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
-        None, description="""Physical group of electrodes."""
-    )
     electrodes: Optional[ExtracellularEphysElectrodes] = Field(
         None, description="""A table of all electrodes (i.e. channels) used for recording."""
     )
+    value: Optional[Dict[str, ElectrodeGroup]] = Field(
+        None, description="""Physical group of electrodes."""
+    )
 
 
 class ExtracellularEphysElectrodes(DynamicTable):
@@ -525,8 +528,14 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    group: List[ElectrodeGroup] = Field(
+    group: VectorData[NDArray[Any, ElectrodeGroup]] = Field(
-        ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
+        ...,
+        description="""Reference to the ElectrodeGroup this electrode is a part of.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
     )
     group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
@@ -583,9 +592,6 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class GeneralIntracellularEphys(ConfiguredBaseModel):
@@ -608,12 +614,12 @@ class GeneralIntracellularEphys(ConfiguredBaseModel):
         None,
         description="""Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries.""",
     )
-    intracellular_electrode: Optional[List[IntracellularElectrode]] = Field(
-        None, description="""An intracellular electrode."""
-    )
     sweep_table: Optional[SweepTable] = Field(
         None, description="""The table which groups different PatchClampSeries together."""
     )
+    value: Optional[Dict[str, IntracellularElectrode]] = Field(
+        None, description="""An intracellular electrode."""
+    )
 
 
 class NWBFileIntervals(ConfiguredBaseModel):
@@ -639,7 +645,7 @@ class NWBFileIntervals(ConfiguredBaseModel):
     invalid_times: Optional[TimeIntervals] = Field(
         None, description="""Time intervals that should be removed from analysis."""
     )
-    time_intervals: Optional[List[TimeIntervals]] = Field(
+    value: Optional[Dict[str, TimeIntervals]] = Field(
         None,
         description="""Optional additional table(s) for describing other experimental time intervals.""",
     )

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_icephys.py

@@ -262,11 +262,21 @@ class PatchClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         ...,
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
     )
-    value: Optional[NDArray[Shape["* num_times"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
         None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
     )
 
@@ -281,12 +291,12 @@ class CurrentClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     bias_current: Optional[float] = Field(None, description="""Bias current, in amps.""")
     bridge_balance: Optional[float] = Field(None, description="""Bridge balance, in ohms.""")
     capacitance_compensation: Optional[float] = Field(
         None, description="""Capacitance compensation, in farads."""
     )
+    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     stimulus_description: str = Field(
         ..., description="""Protocol/stimulus name for this patch-clamp dataset."""
     )
@@ -354,12 +364,24 @@ class CurrentClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IZeroClampSeries(CurrentClampSeries):
@@ -512,6 +534,16 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["amperes"] = Field(
         "amperes",
         description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -519,7 +551,9 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
         },
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class VoltageClampSeries(PatchClampSeries):
@@ -532,13 +566,13 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     capacitance_fast: Optional[VoltageClampSeriesCapacitanceFast] = Field(
         None, description="""Fast capacitance, in farads."""
     )
     capacitance_slow: Optional[VoltageClampSeriesCapacitanceSlow] = Field(
         None, description="""Slow capacitance, in farads."""
     )
+    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     resistance_comp_bandwidth: Optional[VoltageClampSeriesResistanceCompBandwidth] = Field(
         None, description="""Resistance compensation bandwidth, in hertz."""
     )
@@ -610,27 +644,6 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
 
-class VoltageClampSeriesData(ConfiguredBaseModel):
-    """
-    Recorded current.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
-
-    name: Literal["data"] = Field(
-        "data",
-        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
-    )
-    unit: Literal["amperes"] = Field(
-        "amperes",
-        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
-        },
-    )
-    value: Any = Field(...)
-
-
 class VoltageClampSeriesCapacitanceFast(ConfiguredBaseModel):
     """
     Fast capacitance, in farads.
@@ -683,6 +696,39 @@ class VoltageClampSeriesCapacitanceSlow(ConfiguredBaseModel):
     value: float = Field(...)
 
 
+class VoltageClampSeriesData(ConfiguredBaseModel):
+    """
+    Recorded current.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["amperes"] = Field(
+        "amperes",
+        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
+        },
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class VoltageClampSeriesResistanceCompBandwidth(ConfiguredBaseModel):
     """
     Resistance compensation bandwidth, in hertz.
@@ -887,12 +933,24 @@ class VoltageClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IntracellularElectrode(NWBContainer):
@@ -942,18 +1000,15 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: VectorData[NDArray[Any, int]] = Field(
+    series: VectorData[NDArray[Any, PatchClampSeries]] = Field(
         ...,
-        description="""Sweep number of the PatchClampSeries in that row.""",
+        description="""The PatchClampSeries with the sweep number in that row.""",
         json_schema_extra={
             "linkml_meta": {
                 "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
             }
         },
     )
-    series: List[PatchClampSeries] = Field(
-        ..., description="""The PatchClampSeries with the sweep number in that row."""
-    )
     series_index: Named[VectorIndex] = Field(
         ...,
         description="""Index for series.""",
@@ -966,6 +1021,15 @@ class SweepTable(DynamicTable):
             }
         },
     )
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
+        ...,
+        description="""Sweep number of the PatchClampSeries in that row.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -976,9 +1040,6 @@ class SweepTable(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild
@@ -991,9 +1052,9 @@ IZeroClampSeries.model_rebuild()
 CurrentClampStimulusSeries.model_rebuild()
 CurrentClampStimulusSeriesData.model_rebuild()
 VoltageClampSeries.model_rebuild()
-VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesCapacitanceFast.model_rebuild()
 VoltageClampSeriesCapacitanceSlow.model_rebuild()
+VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesResistanceCompBandwidth.model_rebuild()
 VoltageClampSeriesResistanceCompCorrection.model_rebuild()
 VoltageClampSeriesResistanceCompPrediction.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_image.py

@@ -152,7 +152,7 @@ class GrayscaleImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -174,7 +174,7 @@ class RGBImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -204,7 +204,7 @@ class RGBAImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -234,12 +234,9 @@ class ImageSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -250,8 +247,9 @@ class ImageSeries(TimeSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -290,6 +288,39 @@ class ImageSeries(TimeSeries):
     )
 
 
+class ImageSeriesData(ConfiguredBaseModel):
+    """
+    Binary data representing images across frames.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, * z"], float | int],
+        ]
+    ] = Field(None)
+
+
 class ImageSeriesExternalFile(ConfiguredBaseModel):
     """
     Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.
@@ -331,12 +362,9 @@ class ImageMaskSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -347,8 +375,9 @@ class ImageMaskSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -397,6 +426,9 @@ class OpticalSeries(ImageSeries):
     )
 
     name: str = Field(...)
+    data: OpticalSeriesData = Field(
+        ..., description="""Images presented to subject, either grayscale or RGB"""
+    )
     distance: Optional[float] = Field(
         None, description="""Distance from camera/monitor to target/eye."""
     )
@@ -405,10 +437,6 @@ class OpticalSeries(ImageSeries):
             NDArray[Shape["2 width_height"], float], NDArray[Shape["3 width_height_depth"], float]
         ]
     ] = Field(None, description="""Width, height and depth of image, or imaged area, in meters.""")
-    data: Union[
-        NDArray[Shape["* frame, * x, * y"], float],
-        NDArray[Shape["* frame, * x, * y, 3 r_g_b"], float],
-    ] = Field(..., description="""Images presented to subject, either grayscale or RGB""")
     orientation: Optional[str] = Field(
         None,
         description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""",
@@ -423,8 +451,9 @@ class OpticalSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -463,6 +492,39 @@ class OpticalSeries(ImageSeries):
     )
 
 
+class OpticalSeriesData(ConfiguredBaseModel):
+    """
+    Images presented to subject, either grayscale or RGB
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, 3 r_g_b"], float | int],
+        ]
+    ] = Field(None)
+
+
 class IndexSeries(TimeSeries):
     """
     Stores indices to image frames stored in an ImageSeries. The purpose of the ImageIndexSeries is to allow a static image stack to be stored somewhere, and the images in the stack to be referenced out-of-order. This can be for the display of individual images, or of movie segments (as a movie is simply a series of images). The data field stores the index of the frame in the referenced ImageSeries, and the timestamps array indicates when that image was displayed.
@@ -473,10 +535,8 @@ class IndexSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IndexSeriesData = Field(
-        ...,
+        ..., description="""Index of the frame in the referenced ImageSeries."""
-        description="""Index of the frame in the referenced ImageSeries.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     indexed_timeseries: Union[ImageSeries, str] = Field(
         ...,
@@ -524,13 +584,46 @@ class IndexSeries(TimeSeries):
     )
 
 
+class IndexSeriesData(ConfiguredBaseModel):
+    """
+    Index of the frame in the referenced ImageSeries.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 GrayscaleImage.model_rebuild()
 RGBImage.model_rebuild()
 RGBAImage.model_rebuild()
 ImageSeries.model_rebuild()
+ImageSeriesData.model_rebuild()
 ImageSeriesExternalFile.model_rebuild()
 ImageMaskSeries.model_rebuild()
 OpticalSeries.model_rebuild()
+OpticalSeriesData.model_rebuild()
 IndexSeries.model_rebuild()
+IndexSeriesData.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_misc.py

@@ -251,6 +251,16 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "see ",
         description="""Since there can be different units for different features, store the units in 'feature_units'. The default value for this attribute is \"see 'feature_units'\".""",
@@ -258,8 +268,8 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -274,10 +284,8 @@ class AnnotationSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], str] = Field(
+    data: AnnotationSeriesData = Field(
-        ...,
+        ..., description="""Annotations made during an experiment."""
-        description="""Annotations made during an experiment.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -316,6 +324,39 @@ class AnnotationSeries(TimeSeries):
     )
 
 
+class AnnotationSeriesData(ConfiguredBaseModel):
+    """
+    Annotations made during an experiment.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], str]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class IntervalSeries(TimeSeries):
     """
     Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.
@@ -326,10 +367,8 @@ class IntervalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IntervalSeriesData = Field(
-        ...,
+        ..., description="""Use values >0 if interval started, <0 if interval ended."""
-        description="""Use values >0 if interval started, <0 if interval ended.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -368,6 +407,39 @@ class IntervalSeries(TimeSeries):
     )
 
 
+class IntervalSeriesData(ConfiguredBaseModel):
+    """
+    Use values >0 if interval started, <0 if interval ended.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class DecompositionSeries(TimeSeries):
     """
     Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -443,24 +515,36 @@ class DecompositionSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         "no unit",
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"ifabsent": "string(no unit)"}},
     )
-    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float | int]] = (
-        None,
+        Field(
-        json_schema_extra={
+            None,
-            "linkml_meta": {
+            json_schema_extra={
-                "array": {
+                "linkml_meta": {
-                    "dimensions": [
+                    "array": {
-                        {"alias": "num_times"},
+                        "dimensions": [
-                        {"alias": "num_channels"},
+                            {"alias": "num_times"},
-                        {"alias": "num_bands"},
+                            {"alias": "num_channels"},
-                    ]
+                            {"alias": "num_bands"},
+                        ]
+                    }
                 }
-            }
+            },
-        },
+        )
     )
 
 
@@ -518,9 +602,6 @@ class DecompositionSeriesBands(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class Units(DynamicTable):
@@ -533,9 +614,18 @@ class Units(DynamicTable):
     )
 
     name: str = Field("Units", json_schema_extra={"linkml_meta": {"ifabsent": "string(Units)"}})
-    spike_times_index: Optional[Named[VectorIndex]] = Field(
+    electrode_group: Optional[VectorData[NDArray[Any, ElectrodeGroup]]] = Field(
         None,
-        description="""Index into the spike_times dataset.""",
+        description="""Electrode group that each spike unit came from.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
+    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+        None,
+        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -545,12 +635,9 @@ class Units(DynamicTable):
             }
         },
     )
-    spike_times: Optional[UnitsSpikeTimes] = Field(
+    electrodes_index: Optional[Named[VectorIndex]] = Field(
-        None, description="""Spike times for each unit."""
-    )
-    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into the obs_intervals dataset.""",
+        description="""Index into electrodes.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -576,9 +663,9 @@ class Units(DynamicTable):
             },
         )
     )
-    electrodes_index: Optional[Named[VectorIndex]] = Field(
+    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into electrodes.""",
+        description="""Index into the obs_intervals dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -588,9 +675,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+    spike_times: Optional[UnitsSpikeTimes] = Field(
+        None, description="""Spike times for each unit."""
+    )
+    spike_times_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
+        description="""Index into the spike_times dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -600,25 +690,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
+    waveform_mean: Optional[UnitsWaveformMean] = Field(
-        None, description="""Electrode group that each spike unit came from."""
+        None, description="""Spike waveform mean for each spike unit."""
+    )
+    waveform_sd: Optional[UnitsWaveformSd] = Field(
+        None, description="""Spike waveform standard deviation for each spike unit."""
     )
-    waveform_mean: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -629,9 +706,6 @@ class Units(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class UnitsSpikeTimes(VectorData):
@@ -662,14 +736,78 @@ class UnitsSpikeTimes(VectorData):
     ] = Field(None)
 
 
+class UnitsWaveformMean(VectorData):
+    """
+    Spike waveform mean for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_mean"] = Field(
+        "waveform_mean",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_mean", "ifabsent": "string(waveform_mean)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+    value: Optional[
+        Union[
+            NDArray[Shape["* dim0"], Any],
+            NDArray[Shape["* dim0, * dim1"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
+        ]
+    ] = Field(None)
+
+
+class UnitsWaveformSd(VectorData):
+    """
+    Spike waveform standard deviation for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_sd"] = Field(
+        "waveform_sd",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_sd", "ifabsent": "string(waveform_sd)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+    value: Optional[
+        Union[
+            NDArray[Shape["* dim0"], Any],
+            NDArray[Shape["* dim0, * dim1"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
+        ]
+    ] = Field(None)
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 AbstractFeatureSeries.model_rebuild()
 AbstractFeatureSeriesData.model_rebuild()
 AnnotationSeries.model_rebuild()
+AnnotationSeriesData.model_rebuild()
 IntervalSeries.model_rebuild()
+IntervalSeriesData.model_rebuild()
 DecompositionSeries.model_rebuild()
 DecompositionSeriesData.model_rebuild()
 DecompositionSeriesBands.model_rebuild()
 Units.model_rebuild()
 UnitsSpikeTimes.model_rebuild()
+UnitsWaveformMean.model_rebuild()
+UnitsWaveformSd.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_ogen.py

@@ -158,10 +158,8 @@ class OptogeneticSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], float] = Field(
+    data: OptogeneticSeriesData = Field(
-        ...,
+        ..., description="""Applied power for optogenetic stimulus, in watts."""
-        description="""Applied power for optogenetic stimulus, in watts.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     site: Union[OptogeneticStimulusSite, str] = Field(
         ...,
@@ -209,6 +207,37 @@ class OptogeneticSeries(TimeSeries):
     )
 
 
+class OptogeneticSeriesData(ConfiguredBaseModel):
+    """
+    Applied power for optogenetic stimulus, in watts.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ogen"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["watts"] = Field(
+        "watts",
+        description="""Unit of measurement for data, which is fixed to 'watts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "watts", "ifabsent": "string(watts)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class OptogeneticStimulusSite(NWBContainer):
     """
     A site of optogenetic stimulation.
@@ -239,4 +268,5 @@ class OptogeneticStimulusSite(NWBContainer):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 OptogeneticSeries.model_rebuild()
+OptogeneticSeriesData.model_rebuild()
 OptogeneticStimulusSite.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/core_nwb_ophys.py

@@ -28,7 +28,7 @@ from ...core.v2_2_2.core_nwb_base import (
     TimeSeriesSync,
 )
 from ...core.v2_2_2.core_nwb_device import Device
-from ...core.v2_2_2.core_nwb_image import ImageSeries, ImageSeriesExternalFile
+from ...core.v2_2_2.core_nwb_image import ImageSeries, ImageSeriesData, ImageSeriesExternalFile
 from ...hdmf_common.v1_1_3.hdmf_common_table import DynamicTable, DynamicTableRegion
 
 
@@ -209,12 +209,9 @@ class TwoPhotonSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -225,8 +222,9 @@ class TwoPhotonSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -275,9 +273,7 @@ class RoiResponseSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: RoiResponseSeriesData = Field(..., description="""Signals from ROIs.""")
-        NDArray[Shape["* num_times"], float], NDArray[Shape["* num_times, * num_rois"], float]
-    ] = Field(..., description="""Signals from ROIs.""")
     rois: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.""",
@@ -327,6 +323,39 @@ class RoiResponseSeries(TimeSeries):
     )
 
 
+class RoiResponseSeriesData(ConfiguredBaseModel):
+    """
+    Signals from ROIs.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_rois"], float | int],
+        ]
+    ] = Field(None)
+
+
 class DfOverF(NWBDataInterface):
     """
     dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).
@@ -336,10 +365,10 @@ class DfOverF(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field("DfOverF", json_schema_extra={"linkml_meta": {"ifabsent": "string(DfOverF)"}})
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Fluorescence(NWBDataInterface):
@@ -351,10 +380,12 @@ class Fluorescence(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field(
+        "Fluorescence", json_schema_extra={"linkml_meta": {"ifabsent": "string(Fluorescence)"}}
+    )
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ImageSegmentation(NWBDataInterface):
@@ -366,10 +397,13 @@ class ImageSegmentation(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[DynamicTable]] = Field(
+    name: str = Field(
+        "ImageSegmentation",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(ImageSegmentation)"}},
+    )
+    value: Optional[Dict[str, DynamicTable]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "DynamicTable"}]}}
     )
-    name: str = Field(...)
 
 
 class ImagingPlane(NWBContainer):
@@ -538,16 +572,20 @@ class MotionCorrection(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[NWBDataInterface]] = Field(
+    name: str = Field(
+        "MotionCorrection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(MotionCorrection)"}},
+    )
+    value: Optional[Dict[str, NWBDataInterface]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "NWBDataInterface"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 TwoPhotonSeries.model_rebuild()
 RoiResponseSeries.model_rebuild()
+RoiResponseSeriesData.model_rebuild()
 DfOverF.model_rebuild()
 Fluorescence.model_rebuild()
 ImageSegmentation.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_2/namespace.py

@@ -38,6 +38,7 @@ from ...core.v2_2_2.core_nwb_ecephys import (
     ClusterWaveforms,
     Clustering,
     ElectricalSeries,
+    ElectricalSeriesData,
     ElectrodeGroup,
     ElectrodeGroupPosition,
     EventDetection,
@@ -46,6 +47,7 @@ from ...core.v2_2_2.core_nwb_ecephys import (
     FilteredEphys,
     LFP,
     SpikeEventSeries,
+    SpikeEventSeriesData,
 )
 from ...core.v2_2_2.core_nwb_epoch import TimeIntervals, TimeIntervalsTimeseries
 from ...core.v2_2_2.core_nwb_file import (
@@ -85,9 +87,12 @@ from ...core.v2_2_2.core_nwb_image import (
     GrayscaleImage,
     ImageMaskSeries,
     ImageSeries,
+    ImageSeriesData,
     ImageSeriesExternalFile,
     IndexSeries,
+    IndexSeriesData,
     OpticalSeries,
+    OpticalSeriesData,
     RGBAImage,
     RGBImage,
 )
@@ -95,14 +100,22 @@ from ...core.v2_2_2.core_nwb_misc import (
     AbstractFeatureSeries,
     AbstractFeatureSeriesData,
     AnnotationSeries,
+    AnnotationSeriesData,
     DecompositionSeries,
     DecompositionSeriesBands,
     DecompositionSeriesData,
     IntervalSeries,
+    IntervalSeriesData,
     Units,
     UnitsSpikeTimes,
+    UnitsWaveformMean,
+    UnitsWaveformSd,
+)
+from ...core.v2_2_2.core_nwb_ogen import (
+    OptogeneticSeries,
+    OptogeneticSeriesData,
+    OptogeneticStimulusSite,
 )
-from ...core.v2_2_2.core_nwb_ogen import OptogeneticSeries, OptogeneticStimulusSite
 from ...core.v2_2_2.core_nwb_ophys import (
     DfOverF,
     Fluorescence,
@@ -114,6 +127,7 @@ from ...core.v2_2_2.core_nwb_ophys import (
     MotionCorrection,
     OpticalChannel,
     RoiResponseSeries,
+    RoiResponseSeriesData,
     TwoPhotonSeries,
 )
 from ...core.v2_2_2.core_nwb_retinotopy import (

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_base.py

@@ -170,9 +170,9 @@ class Image(NWBData):
     description: Optional[str] = Field(None, description="""Description of the image.""")
     value: Optional[
         Union[
-            NDArray[Shape["* x, * y"], float],
+            NDArray[Shape["* x, * y"], float | int],
-            NDArray[Shape["* x, * y, 3 r_g_b"], float],
+            NDArray[Shape["* x, * y, 3 r_g_b"], float | int],
-            NDArray[Shape["* x, * y, 4 r_g_b_a"], float],
+            NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int],
         ]
     ] = Field(None)
 
@@ -333,13 +333,16 @@ class ProcessingModule(NWBContainer):
         {"from_schema": "core.nwb.base", "tree_root": True}
     )
 
-    value: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    name: str = Field(...)
+    description: str = Field(
+        ..., description="""Description of this collection of processed data."""
+    )
+    value: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    name: str = Field(...)
 
 
 class Images(NWBDataInterface):
@@ -353,7 +356,7 @@ class Images(NWBDataInterface):
 
     name: str = Field("Images", json_schema_extra={"linkml_meta": {"ifabsent": "string(Images)"}})
     description: str = Field(..., description="""Description of this collection of images.""")
-    image: List[Image] = Field(..., description="""Images stored in this collection.""")
+    image: List[str] = Field(..., description="""Images stored in this collection.""")
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_behavior.py

@@ -213,6 +213,16 @@ class SpatialSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "meters",
         description="""Base unit of measurement for working with the data. The default value is 'meters'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -220,8 +230,8 @@ class SpatialSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -235,10 +245,13 @@ class BehavioralEpochs(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[IntervalSeries]] = Field(
+    name: str = Field(
+        "BehavioralEpochs",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEpochs)"}},
+    )
+    value: Optional[Dict[str, IntervalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "IntervalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralEvents(NWBDataInterface):
@@ -250,10 +263,13 @@ class BehavioralEvents(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralEvents",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEvents)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralTimeSeries(NWBDataInterface):
@@ -265,10 +281,13 @@ class BehavioralTimeSeries(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralTimeSeries",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralTimeSeries)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class PupilTracking(NWBDataInterface):
@@ -280,10 +299,12 @@ class PupilTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "PupilTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(PupilTracking)"}}
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class EyeTracking(NWBDataInterface):
@@ -295,10 +316,12 @@ class EyeTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "EyeTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(EyeTracking)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class CompassDirection(NWBDataInterface):
@@ -310,10 +333,13 @@ class CompassDirection(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "CompassDirection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(CompassDirection)"}},
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Position(NWBDataInterface):
@@ -325,10 +351,12 @@ class Position(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "Position", json_schema_extra={"linkml_meta": {"ifabsent": "string(Position)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_ecephys.py

@@ -190,11 +190,12 @@ class ElectricalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        NDArray[Shape["* num_times"], float],
+        None,
-        NDArray[Shape["* num_times, * num_channels"], float],
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        NDArray[Shape["* num_times, * num_channels, * num_samples"], float],
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    ] = Field(..., description="""Recorded voltage data.""")
+    )
+    data: ElectricalSeriesData = Field(..., description="""Recorded voltage data.""")
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -207,11 +208,6 @@ class ElectricalSeries(TimeSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -249,6 +245,41 @@ class ElectricalSeries(TimeSeries):
     )
 
 
+class ElectricalSeriesData(ConfiguredBaseModel):
+    """
+    Recorded voltage data.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Base unit of measurement for working with the data. This value is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and 'channel_conversion' (if present).""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_channels"], float | int],
+            NDArray[Shape["* num_times, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class SpikeEventSeries(ElectricalSeries):
     """
     Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).
@@ -259,15 +290,17 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: SpikeEventSeriesData = Field(..., description="""Spike waveforms.""")
-        NDArray[Shape["* num_events, * num_samples"], float],
-        NDArray[Shape["* num_events, * num_channels, * num_samples"], float],
-    ] = Field(..., description="""Spike waveforms.""")
     timestamps: NDArray[Shape["* num_times"], float] = Field(
         ...,
         description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
+        None,
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
+    )
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -280,11 +313,6 @@ class SpikeEventSeries(ElectricalSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -317,6 +345,40 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
 
+class SpikeEventSeriesData(ConfiguredBaseModel):
+    """
+    Spike waveforms.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Unit of measurement for waveforms, which is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_events, * num_samples"], float | int],
+            NDArray[Shape["* num_events, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class FeatureExtraction(NWBDataInterface):
     """
     Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.
@@ -415,10 +477,12 @@ class EventWaveform(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[SpikeEventSeries]] = Field(
+    name: str = Field(
+        "EventWaveform", json_schema_extra={"linkml_meta": {"ifabsent": "string(EventWaveform)"}}
+    )
+    value: Optional[Dict[str, SpikeEventSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpikeEventSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class FilteredEphys(NWBDataInterface):
@@ -430,10 +494,12 @@ class FilteredEphys(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field(
+        "FilteredEphys", json_schema_extra={"linkml_meta": {"ifabsent": "string(FilteredEphys)"}}
+    )
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class LFP(NWBDataInterface):
@@ -445,10 +511,10 @@ class LFP(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field("LFP", json_schema_extra={"linkml_meta": {"ifabsent": "string(LFP)"}})
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ElectrodeGroup(NWBContainer):
@@ -591,7 +657,9 @@ class Clustering(NWBDataInterface):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 ElectricalSeries.model_rebuild()
+ElectricalSeriesData.model_rebuild()
 SpikeEventSeries.model_rebuild()
+SpikeEventSeriesData.model_rebuild()
 FeatureExtraction.model_rebuild()
 EventDetection.model_rebuild()
 EventWaveform.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_epoch.py

@@ -247,9 +247,6 @@ class TimeIntervals(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class TimeIntervalsTimeseries(VectorData):

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_file.py

@@ -225,28 +225,28 @@ class NWBFile(NWBContainer):
         ...,
         description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""",
     )
-    acquisition: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    acquisition: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    analysis: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    analysis: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    scratch: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    scratch: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    processing: Optional[List[ProcessingModule]] = Field(
+    processing: Optional[Dict[str, ProcessingModule]] = Field(
         None,
         description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ProcessingModule"}]}},
@@ -264,6 +264,9 @@ class NWBFile(NWBContainer):
         description="""Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.""",
     )
     units: Optional[Units] = Field(None, description="""Data about sorted spike units.""")
+    specifications: Optional[dict] = Field(
+        None, description="""Nested dictionary of schema specifications"""
+    )
 
 
 class NWBFileStimulus(ConfiguredBaseModel):
@@ -279,12 +282,12 @@ class NWBFileStimulus(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "stimulus", "ifabsent": "string(stimulus)"}
         },
     )
-    presentation: Optional[List[TimeSeries]] = Field(
+    presentation: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Stimuli presented during the experiment.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
     )
-    templates: Optional[List[TimeSeries]] = Field(
+    templates: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
@@ -362,11 +365,7 @@ class NWBFileGeneral(ConfiguredBaseModel):
         None,
         description="""Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc.""",
     )
-    lab_meta_data: Optional[List[LabMetaData]] = Field(
+    devices: Optional[Dict[str, Device]] = Field(
-        None,
-        description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
-    )
-    devices: Optional[List[Device]] = Field(
         None,
         description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "Device"}]}},
@@ -381,16 +380,20 @@ class NWBFileGeneral(ConfiguredBaseModel):
     intracellular_ephys: Optional[GeneralIntracellularEphys] = Field(
         None, description="""Metadata related to intracellular electrophysiology."""
     )
-    optogenetics: Optional[List[OptogeneticStimulusSite]] = Field(
+    optogenetics: Optional[Dict[str, OptogeneticStimulusSite]] = Field(
         None,
         description="""Metadata describing optogenetic stimuluation.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "OptogeneticStimulusSite"}]}},
     )
-    optophysiology: Optional[List[ImagingPlane]] = Field(
+    optophysiology: Optional[Dict[str, ImagingPlane]] = Field(
         None,
         description="""Metadata related to optophysiology.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImagingPlane"}]}},
     )
+    value: Optional[Dict[str, LabMetaData]] = Field(
+        None,
+        description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
+    )
 
 
 class GeneralSourceScript(ConfiguredBaseModel):
@@ -426,12 +429,12 @@ class GeneralExtracellularEphys(ConfiguredBaseModel):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
-        None, description="""Physical group of electrodes."""
-    )
     electrodes: Optional[ExtracellularEphysElectrodes] = Field(
         None, description="""A table of all electrodes (i.e. channels) used for recording."""
     )
+    value: Optional[Dict[str, ElectrodeGroup]] = Field(
+        None, description="""Physical group of electrodes."""
+    )
 
 
 class ExtracellularEphysElectrodes(DynamicTable):
@@ -501,8 +504,14 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    group: List[ElectrodeGroup] = Field(
+    group: VectorData[NDArray[Any, ElectrodeGroup]] = Field(
-        ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
+        ...,
+        description="""Reference to the ElectrodeGroup this electrode is a part of.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
     )
     group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
@@ -559,9 +568,6 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class GeneralIntracellularEphys(ConfiguredBaseModel):
@@ -584,12 +590,12 @@ class GeneralIntracellularEphys(ConfiguredBaseModel):
         None,
         description="""Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries.""",
     )
-    intracellular_electrode: Optional[List[IntracellularElectrode]] = Field(
-        None, description="""An intracellular electrode."""
-    )
     sweep_table: Optional[SweepTable] = Field(
         None, description="""The table which groups different PatchClampSeries together."""
     )
+    value: Optional[Dict[str, IntracellularElectrode]] = Field(
+        None, description="""An intracellular electrode."""
+    )
 
 
 class NWBFileIntervals(ConfiguredBaseModel):
@@ -615,7 +621,7 @@ class NWBFileIntervals(ConfiguredBaseModel):
     invalid_times: Optional[TimeIntervals] = Field(
         None, description="""Time intervals that should be removed from analysis."""
     )
-    time_intervals: Optional[List[TimeIntervals]] = Field(
+    value: Optional[Dict[str, TimeIntervals]] = Field(
         None,
         description="""Optional additional table(s) for describing other experimental time intervals.""",
     )

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_icephys.py

@@ -262,11 +262,21 @@ class PatchClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         ...,
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
     )
-    value: Optional[NDArray[Shape["* num_times"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
         None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
     )
 
@@ -281,12 +291,12 @@ class CurrentClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     bias_current: Optional[float] = Field(None, description="""Bias current, in amps.""")
     bridge_balance: Optional[float] = Field(None, description="""Bridge balance, in ohms.""")
     capacitance_compensation: Optional[float] = Field(
         None, description="""Capacitance compensation, in farads."""
     )
+    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     stimulus_description: str = Field(
         ..., description="""Protocol/stimulus name for this patch-clamp dataset."""
     )
@@ -354,12 +364,24 @@ class CurrentClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IZeroClampSeries(CurrentClampSeries):
@@ -512,6 +534,16 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["amperes"] = Field(
         "amperes",
         description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -519,7 +551,9 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
         },
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class VoltageClampSeries(PatchClampSeries):
@@ -532,13 +566,13 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     capacitance_fast: Optional[VoltageClampSeriesCapacitanceFast] = Field(
         None, description="""Fast capacitance, in farads."""
     )
     capacitance_slow: Optional[VoltageClampSeriesCapacitanceSlow] = Field(
         None, description="""Slow capacitance, in farads."""
     )
+    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     resistance_comp_bandwidth: Optional[VoltageClampSeriesResistanceCompBandwidth] = Field(
         None, description="""Resistance compensation bandwidth, in hertz."""
     )
@@ -610,27 +644,6 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
 
-class VoltageClampSeriesData(ConfiguredBaseModel):
-    """
-    Recorded current.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
-
-    name: Literal["data"] = Field(
-        "data",
-        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
-    )
-    unit: Literal["amperes"] = Field(
-        "amperes",
-        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
-        },
-    )
-    value: Any = Field(...)
-
-
 class VoltageClampSeriesCapacitanceFast(ConfiguredBaseModel):
     """
     Fast capacitance, in farads.
@@ -683,6 +696,39 @@ class VoltageClampSeriesCapacitanceSlow(ConfiguredBaseModel):
     value: float = Field(...)
 
 
+class VoltageClampSeriesData(ConfiguredBaseModel):
+    """
+    Recorded current.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["amperes"] = Field(
+        "amperes",
+        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
+        },
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class VoltageClampSeriesResistanceCompBandwidth(ConfiguredBaseModel):
     """
     Resistance compensation bandwidth, in hertz.
@@ -887,12 +933,24 @@ class VoltageClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IntracellularElectrode(NWBContainer):
@@ -942,18 +1000,15 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: VectorData[NDArray[Any, int]] = Field(
+    series: VectorData[NDArray[Any, PatchClampSeries]] = Field(
         ...,
-        description="""Sweep number of the PatchClampSeries in that row.""",
+        description="""The PatchClampSeries with the sweep number in that row.""",
         json_schema_extra={
             "linkml_meta": {
                 "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
             }
         },
     )
-    series: List[PatchClampSeries] = Field(
-        ..., description="""The PatchClampSeries with the sweep number in that row."""
-    )
     series_index: Named[VectorIndex] = Field(
         ...,
         description="""Index for series.""",
@@ -966,6 +1021,15 @@ class SweepTable(DynamicTable):
             }
         },
     )
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
+        ...,
+        description="""Sweep number of the PatchClampSeries in that row.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -976,9 +1040,6 @@ class SweepTable(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild
@@ -991,9 +1052,9 @@ IZeroClampSeries.model_rebuild()
 CurrentClampStimulusSeries.model_rebuild()
 CurrentClampStimulusSeriesData.model_rebuild()
 VoltageClampSeries.model_rebuild()
-VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesCapacitanceFast.model_rebuild()
 VoltageClampSeriesCapacitanceSlow.model_rebuild()
+VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesResistanceCompBandwidth.model_rebuild()
 VoltageClampSeriesResistanceCompCorrection.model_rebuild()
 VoltageClampSeriesResistanceCompPrediction.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_image.py

@@ -152,7 +152,7 @@ class GrayscaleImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -174,7 +174,7 @@ class RGBImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -204,7 +204,7 @@ class RGBAImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -234,12 +234,9 @@ class ImageSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -250,8 +247,9 @@ class ImageSeries(TimeSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -290,6 +288,39 @@ class ImageSeries(TimeSeries):
     )
 
 
+class ImageSeriesData(ConfiguredBaseModel):
+    """
+    Binary data representing images across frames.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, * z"], float | int],
+        ]
+    ] = Field(None)
+
+
 class ImageSeriesExternalFile(ConfiguredBaseModel):
     """
     Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.
@@ -331,12 +362,9 @@ class ImageMaskSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -347,8 +375,9 @@ class ImageMaskSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -397,6 +426,9 @@ class OpticalSeries(ImageSeries):
     )
 
     name: str = Field(...)
+    data: OpticalSeriesData = Field(
+        ..., description="""Images presented to subject, either grayscale or RGB"""
+    )
     distance: Optional[float] = Field(
         None, description="""Distance from camera/monitor to target/eye."""
     )
@@ -405,10 +437,6 @@ class OpticalSeries(ImageSeries):
             NDArray[Shape["2 width_height"], float], NDArray[Shape["3 width_height_depth"], float]
         ]
     ] = Field(None, description="""Width, height and depth of image, or imaged area, in meters.""")
-    data: Union[
-        NDArray[Shape["* frame, * x, * y"], float],
-        NDArray[Shape["* frame, * x, * y, 3 r_g_b"], float],
-    ] = Field(..., description="""Images presented to subject, either grayscale or RGB""")
     orientation: Optional[str] = Field(
         None,
         description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""",
@@ -423,8 +451,9 @@ class OpticalSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -463,6 +492,39 @@ class OpticalSeries(ImageSeries):
     )
 
 
+class OpticalSeriesData(ConfiguredBaseModel):
+    """
+    Images presented to subject, either grayscale or RGB
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, 3 r_g_b"], float | int],
+        ]
+    ] = Field(None)
+
+
 class IndexSeries(TimeSeries):
     """
     Stores indices to image frames stored in an ImageSeries. The purpose of the ImageIndexSeries is to allow a static image stack to be stored somewhere, and the images in the stack to be referenced out-of-order. This can be for the display of individual images, or of movie segments (as a movie is simply a series of images). The data field stores the index of the frame in the referenced ImageSeries, and the timestamps array indicates when that image was displayed.
@@ -473,10 +535,8 @@ class IndexSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IndexSeriesData = Field(
-        ...,
+        ..., description="""Index of the frame in the referenced ImageSeries."""
-        description="""Index of the frame in the referenced ImageSeries.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     indexed_timeseries: Union[ImageSeries, str] = Field(
         ...,
@@ -524,13 +584,46 @@ class IndexSeries(TimeSeries):
     )
 
 
+class IndexSeriesData(ConfiguredBaseModel):
+    """
+    Index of the frame in the referenced ImageSeries.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 GrayscaleImage.model_rebuild()
 RGBImage.model_rebuild()
 RGBAImage.model_rebuild()
 ImageSeries.model_rebuild()
+ImageSeriesData.model_rebuild()
 ImageSeriesExternalFile.model_rebuild()
 ImageMaskSeries.model_rebuild()
 OpticalSeries.model_rebuild()
+OpticalSeriesData.model_rebuild()
 IndexSeries.model_rebuild()
+IndexSeriesData.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_misc.py

@@ -251,6 +251,16 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "see ",
         description="""Since there can be different units for different features, store the units in 'feature_units'. The default value for this attribute is \"see 'feature_units'\".""",
@@ -258,8 +268,8 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -274,10 +284,8 @@ class AnnotationSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], str] = Field(
+    data: AnnotationSeriesData = Field(
-        ...,
+        ..., description="""Annotations made during an experiment."""
-        description="""Annotations made during an experiment.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -316,6 +324,39 @@ class AnnotationSeries(TimeSeries):
     )
 
 
+class AnnotationSeriesData(ConfiguredBaseModel):
+    """
+    Annotations made during an experiment.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], str]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class IntervalSeries(TimeSeries):
     """
     Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.
@@ -326,10 +367,8 @@ class IntervalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IntervalSeriesData = Field(
-        ...,
+        ..., description="""Use values >0 if interval started, <0 if interval ended."""
-        description="""Use values >0 if interval started, <0 if interval ended.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -368,6 +407,39 @@ class IntervalSeries(TimeSeries):
     )
 
 
+class IntervalSeriesData(ConfiguredBaseModel):
+    """
+    Use values >0 if interval started, <0 if interval ended.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class DecompositionSeries(TimeSeries):
     """
     Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -443,24 +515,36 @@ class DecompositionSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         "no unit",
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"ifabsent": "string(no unit)"}},
     )
-    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float | int]] = (
-        None,
+        Field(
-        json_schema_extra={
+            None,
-            "linkml_meta": {
+            json_schema_extra={
-                "array": {
+                "linkml_meta": {
-                    "dimensions": [
+                    "array": {
-                        {"alias": "num_times"},
+                        "dimensions": [
-                        {"alias": "num_channels"},
+                            {"alias": "num_times"},
-                        {"alias": "num_bands"},
+                            {"alias": "num_channels"},
-                    ]
+                            {"alias": "num_bands"},
+                        ]
+                    }
                 }
-            }
+            },
-        },
+        )
     )
 
 
@@ -518,9 +602,6 @@ class DecompositionSeriesBands(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class Units(DynamicTable):
@@ -533,9 +614,18 @@ class Units(DynamicTable):
     )
 
     name: str = Field("Units", json_schema_extra={"linkml_meta": {"ifabsent": "string(Units)"}})
-    spike_times_index: Optional[Named[VectorIndex]] = Field(
+    electrode_group: Optional[VectorData[NDArray[Any, ElectrodeGroup]]] = Field(
         None,
-        description="""Index into the spike_times dataset.""",
+        description="""Electrode group that each spike unit came from.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
+    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+        None,
+        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -545,12 +635,9 @@ class Units(DynamicTable):
             }
         },
     )
-    spike_times: Optional[UnitsSpikeTimes] = Field(
+    electrodes_index: Optional[Named[VectorIndex]] = Field(
-        None, description="""Spike times for each unit."""
-    )
-    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into the obs_intervals dataset.""",
+        description="""Index into electrodes.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -576,9 +663,9 @@ class Units(DynamicTable):
             },
         )
     )
-    electrodes_index: Optional[Named[VectorIndex]] = Field(
+    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into electrodes.""",
+        description="""Index into the obs_intervals dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -588,9 +675,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+    spike_times: Optional[UnitsSpikeTimes] = Field(
+        None, description="""Spike times for each unit."""
+    )
+    spike_times_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
+        description="""Index into the spike_times dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -600,25 +690,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
+    waveform_mean: Optional[UnitsWaveformMean] = Field(
-        None, description="""Electrode group that each spike unit came from."""
+        None, description="""Spike waveform mean for each spike unit."""
+    )
+    waveform_sd: Optional[UnitsWaveformSd] = Field(
+        None, description="""Spike waveform standard deviation for each spike unit."""
     )
-    waveform_mean: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -629,9 +706,6 @@ class Units(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class UnitsSpikeTimes(VectorData):
@@ -662,14 +736,78 @@ class UnitsSpikeTimes(VectorData):
     ] = Field(None)
 
 
+class UnitsWaveformMean(VectorData):
+    """
+    Spike waveform mean for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_mean"] = Field(
+        "waveform_mean",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_mean", "ifabsent": "string(waveform_mean)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+    value: Optional[
+        Union[
+            NDArray[Shape["* dim0"], Any],
+            NDArray[Shape["* dim0, * dim1"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
+        ]
+    ] = Field(None)
+
+
+class UnitsWaveformSd(VectorData):
+    """
+    Spike waveform standard deviation for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_sd"] = Field(
+        "waveform_sd",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_sd", "ifabsent": "string(waveform_sd)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+    value: Optional[
+        Union[
+            NDArray[Shape["* dim0"], Any],
+            NDArray[Shape["* dim0, * dim1"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
+        ]
+    ] = Field(None)
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 AbstractFeatureSeries.model_rebuild()
 AbstractFeatureSeriesData.model_rebuild()
 AnnotationSeries.model_rebuild()
+AnnotationSeriesData.model_rebuild()
 IntervalSeries.model_rebuild()
+IntervalSeriesData.model_rebuild()
 DecompositionSeries.model_rebuild()
 DecompositionSeriesData.model_rebuild()
 DecompositionSeriesBands.model_rebuild()
 Units.model_rebuild()
 UnitsSpikeTimes.model_rebuild()
+UnitsWaveformMean.model_rebuild()
+UnitsWaveformSd.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_ogen.py

@@ -158,10 +158,8 @@ class OptogeneticSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], float] = Field(
+    data: OptogeneticSeriesData = Field(
-        ...,
+        ..., description="""Applied power for optogenetic stimulus, in watts."""
-        description="""Applied power for optogenetic stimulus, in watts.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     site: Union[OptogeneticStimulusSite, str] = Field(
         ...,
@@ -209,6 +207,37 @@ class OptogeneticSeries(TimeSeries):
     )
 
 
+class OptogeneticSeriesData(ConfiguredBaseModel):
+    """
+    Applied power for optogenetic stimulus, in watts.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ogen"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["watts"] = Field(
+        "watts",
+        description="""Unit of measurement for data, which is fixed to 'watts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "watts", "ifabsent": "string(watts)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class OptogeneticStimulusSite(NWBContainer):
     """
     A site of optogenetic stimulation.
@@ -239,4 +268,5 @@ class OptogeneticStimulusSite(NWBContainer):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 OptogeneticSeries.model_rebuild()
+OptogeneticSeriesData.model_rebuild()
 OptogeneticStimulusSite.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/core_nwb_ophys.py

@@ -28,7 +28,7 @@ from ...core.v2_2_4.core_nwb_base import (
     TimeSeriesSync,
 )
 from ...core.v2_2_4.core_nwb_device import Device
-from ...core.v2_2_4.core_nwb_image import ImageSeries, ImageSeriesExternalFile
+from ...core.v2_2_4.core_nwb_image import ImageSeries, ImageSeriesData, ImageSeriesExternalFile
 from ...hdmf_common.v1_1_3.hdmf_common_table import (
     DynamicTable,
     DynamicTableRegion,
@@ -215,12 +215,9 @@ class TwoPhotonSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -231,8 +228,9 @@ class TwoPhotonSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -281,9 +279,7 @@ class RoiResponseSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: RoiResponseSeriesData = Field(..., description="""Signals from ROIs.""")
-        NDArray[Shape["* num_times"], float], NDArray[Shape["* num_times, * num_rois"], float]
-    ] = Field(..., description="""Signals from ROIs.""")
     rois: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.""",
@@ -333,6 +329,39 @@ class RoiResponseSeries(TimeSeries):
     )
 
 
+class RoiResponseSeriesData(ConfiguredBaseModel):
+    """
+    Signals from ROIs.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_rois"], float | int],
+        ]
+    ] = Field(None)
+
+
 class DfOverF(NWBDataInterface):
     """
     dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).
@@ -342,10 +371,10 @@ class DfOverF(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field("DfOverF", json_schema_extra={"linkml_meta": {"ifabsent": "string(DfOverF)"}})
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Fluorescence(NWBDataInterface):
@@ -357,10 +386,12 @@ class Fluorescence(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field(
+        "Fluorescence", json_schema_extra={"linkml_meta": {"ifabsent": "string(Fluorescence)"}}
+    )
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ImageSegmentation(NWBDataInterface):
@@ -372,10 +403,13 @@ class ImageSegmentation(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[PlaneSegmentation]] = Field(
+    name: str = Field(
+        "ImageSegmentation",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(ImageSegmentation)"}},
+    )
+    value: Optional[Dict[str, PlaneSegmentation]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "PlaneSegmentation"}]}}
     )
-    name: str = Field(...)
 
 
 class PlaneSegmentation(DynamicTable):
@@ -388,10 +422,21 @@ class PlaneSegmentation(DynamicTable):
     )
 
     name: str = Field(...)
-    image_mask: Optional[PlaneSegmentationImageMask] = Field(
+    image_mask: Optional[
+        VectorData[
+            Union[
+                NDArray[Shape["* num_roi, * num_x, * num_y"], Any],
+                NDArray[Shape["* num_roi, * num_x, * num_y, * num_z"], Any],
+            ]
+        ]
+    ] = Field(
         None,
         description="""ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero.""",
     )
+    pixel_mask: Optional[PlaneSegmentationPixelMask] = Field(
+        None,
+        description="""Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
+    )
     pixel_mask_index: Optional[Named[VectorIndex]] = Field(
         None,
         description="""Index into pixel_mask.""",
@@ -404,9 +449,9 @@ class PlaneSegmentation(DynamicTable):
             }
         },
     )
-    pixel_mask: Optional[PlaneSegmentationPixelMask] = Field(
+    voxel_mask: Optional[PlaneSegmentationVoxelMask] = Field(
         None,
-        description="""Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
+        description="""Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
     )
     voxel_mask_index: Optional[Named[VectorIndex]] = Field(
         None,
@@ -420,11 +465,7 @@ class PlaneSegmentation(DynamicTable):
             }
         },
     )
-    voxel_mask: Optional[PlaneSegmentationVoxelMask] = Field(
+    reference_images: Optional[Dict[str, ImageSeries]] = Field(
-        None,
-        description="""Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
-    )
-    reference_images: Optional[List[ImageSeries]] = Field(
         None,
         description="""Image stacks that the segmentation masks apply to.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImageSeries"}]}},
@@ -448,33 +489,6 @@ class PlaneSegmentation(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
-
-
-class PlaneSegmentationImageMask(VectorData):
-    """
-    ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
-
-    name: Literal["image_mask"] = Field(
-        "image_mask",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "image_mask", "ifabsent": "string(image_mask)"}
-        },
-    )
-    description: str = Field(..., description="""Description of what these vectors represent.""")
-    value: Optional[
-        Union[
-            NDArray[Shape["* dim0"], Any],
-            NDArray[Shape["* dim0, * dim1"], Any],
-            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
-            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
-        ]
-    ] = Field(None)
 
 
 class PlaneSegmentationPixelMask(VectorData):
@@ -597,7 +611,7 @@ class ImagingPlane(NWBContainer):
         None,
         description="""Describes reference frame of origin_coords and grid_spacing. For example, this can be a text description of the anatomical location and orientation of the grid defined by origin_coords and grid_spacing or the vectors needed to transform or rotate the grid to a common anatomical axis (e.g., AP/DV/ML). This field is necessary to interpret origin_coords and grid_spacing. If origin_coords and grid_spacing are not present, then this field is not required. For example, if the microscope takes 10 x 10 x 2 images, where the first value of the data matrix (index (0, 0, 0)) corresponds to (-1.2, -0.6, -2) mm relative to bregma, the spacing between pixels is 0.2 mm in x, 0.2 mm in y and 0.5 mm in z, and larger numbers in x means more anterior, larger numbers in y means more rightward, and larger numbers in z means more ventral, then enter the following -- origin_coords = (-1.2, -0.6, -2) grid_spacing = (0.2, 0.2, 0.5) reference_frame = \"Origin coordinates are relative to bregma. First dimension corresponds to anterior-posterior axis (larger index = more anterior). Second dimension corresponds to medial-lateral axis (larger index = more rightward). Third dimension corresponds to dorsal-ventral axis (larger index = more ventral).\"""",
     )
-    optical_channel: List[OpticalChannel] = Field(
+    optical_channel: Dict[str, OpticalChannel] = Field(
         ..., description="""An optical channel used to record from an imaging plane."""
     )
     device: Union[Device, str] = Field(
@@ -731,10 +745,13 @@ class MotionCorrection(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[CorrectedImageStack]] = Field(
+    name: str = Field(
+        "MotionCorrection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(MotionCorrection)"}},
+    )
+    value: Optional[Dict[str, CorrectedImageStack]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "CorrectedImageStack"}]}}
     )
-    name: str = Field(...)
 
 
 class CorrectedImageStack(NWBDataInterface):
@@ -769,11 +786,11 @@ class CorrectedImageStack(NWBDataInterface):
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 TwoPhotonSeries.model_rebuild()
 RoiResponseSeries.model_rebuild()
+RoiResponseSeriesData.model_rebuild()
 DfOverF.model_rebuild()
 Fluorescence.model_rebuild()
 ImageSegmentation.model_rebuild()
 PlaneSegmentation.model_rebuild()
-PlaneSegmentationImageMask.model_rebuild()
 PlaneSegmentationPixelMask.model_rebuild()
 PlaneSegmentationVoxelMask.model_rebuild()
 ImagingPlane.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_4/namespace.py

@@ -38,6 +38,7 @@ from ...core.v2_2_4.core_nwb_ecephys import (
     ClusterWaveforms,
     Clustering,
     ElectricalSeries,
+    ElectricalSeriesData,
     ElectrodeGroup,
     ElectrodeGroupPosition,
     EventDetection,
@@ -46,6 +47,7 @@ from ...core.v2_2_4.core_nwb_ecephys import (
     FilteredEphys,
     LFP,
     SpikeEventSeries,
+    SpikeEventSeriesData,
 )
 from ...core.v2_2_4.core_nwb_epoch import TimeIntervals, TimeIntervalsTimeseries
 from ...core.v2_2_4.core_nwb_file import (
@@ -87,9 +89,12 @@ from ...core.v2_2_4.core_nwb_image import (
     GrayscaleImage,
     ImageMaskSeries,
     ImageSeries,
+    ImageSeriesData,
     ImageSeriesExternalFile,
     IndexSeries,
+    IndexSeriesData,
     OpticalSeries,
+    OpticalSeriesData,
     RGBAImage,
     RGBImage,
 )
@@ -97,14 +102,22 @@ from ...core.v2_2_4.core_nwb_misc import (
     AbstractFeatureSeries,
     AbstractFeatureSeriesData,
     AnnotationSeries,
+    AnnotationSeriesData,
     DecompositionSeries,
     DecompositionSeriesBands,
     DecompositionSeriesData,
     IntervalSeries,
+    IntervalSeriesData,
     Units,
     UnitsSpikeTimes,
+    UnitsWaveformMean,
+    UnitsWaveformSd,
+)
+from ...core.v2_2_4.core_nwb_ogen import (
+    OptogeneticSeries,
+    OptogeneticSeriesData,
+    OptogeneticStimulusSite,
 )
-from ...core.v2_2_4.core_nwb_ogen import OptogeneticSeries, OptogeneticStimulusSite
 from ...core.v2_2_4.core_nwb_ophys import (
     CorrectedImageStack,
     DfOverF,
@@ -117,10 +130,10 @@ from ...core.v2_2_4.core_nwb_ophys import (
     MotionCorrection,
     OpticalChannel,
     PlaneSegmentation,
-    PlaneSegmentationImageMask,
     PlaneSegmentationPixelMask,
     PlaneSegmentationVoxelMask,
     RoiResponseSeries,
+    RoiResponseSeriesData,
     TwoPhotonSeries,
 )
 from ...core.v2_2_4.core_nwb_retinotopy import (

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_base.py

@@ -170,9 +170,9 @@ class Image(NWBData):
     description: Optional[str] = Field(None, description="""Description of the image.""")
     value: Optional[
         Union[
-            NDArray[Shape["* x, * y"], float],
+            NDArray[Shape["* x, * y"], float | int],
-            NDArray[Shape["* x, * y, 3 r_g_b"], float],
+            NDArray[Shape["* x, * y, 3 r_g_b"], float | int],
-            NDArray[Shape["* x, * y, 4 r_g_b_a"], float],
+            NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int],
         ]
     ] = Field(None)
 
@@ -333,13 +333,16 @@ class ProcessingModule(NWBContainer):
         {"from_schema": "core.nwb.base", "tree_root": True}
     )
 
-    value: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    name: str = Field(...)
+    description: str = Field(
+        ..., description="""Description of this collection of processed data."""
+    )
+    value: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    name: str = Field(...)
 
 
 class Images(NWBDataInterface):
@@ -353,7 +356,7 @@ class Images(NWBDataInterface):
 
     name: str = Field("Images", json_schema_extra={"linkml_meta": {"ifabsent": "string(Images)"}})
     description: str = Field(..., description="""Description of this collection of images.""")
-    image: List[Image] = Field(..., description="""Images stored in this collection.""")
+    image: List[str] = Field(..., description="""Images stored in this collection.""")
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_behavior.py

@@ -213,6 +213,16 @@ class SpatialSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "meters",
         description="""Base unit of measurement for working with the data. The default value is 'meters'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -220,8 +230,8 @@ class SpatialSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -235,10 +245,13 @@ class BehavioralEpochs(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[IntervalSeries]] = Field(
+    name: str = Field(
+        "BehavioralEpochs",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEpochs)"}},
+    )
+    value: Optional[Dict[str, IntervalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "IntervalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralEvents(NWBDataInterface):
@@ -250,10 +263,13 @@ class BehavioralEvents(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralEvents",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralEvents)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class BehavioralTimeSeries(NWBDataInterface):
@@ -265,10 +281,13 @@ class BehavioralTimeSeries(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "BehavioralTimeSeries",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(BehavioralTimeSeries)"}},
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class PupilTracking(NWBDataInterface):
@@ -280,10 +299,12 @@ class PupilTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[TimeSeries]] = Field(
+    name: str = Field(
+        "PupilTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(PupilTracking)"}}
+    )
+    value: Optional[Dict[str, TimeSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class EyeTracking(NWBDataInterface):
@@ -295,10 +316,12 @@ class EyeTracking(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "EyeTracking", json_schema_extra={"linkml_meta": {"ifabsent": "string(EyeTracking)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class CompassDirection(NWBDataInterface):
@@ -310,10 +333,13 @@ class CompassDirection(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "CompassDirection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(CompassDirection)"}},
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Position(NWBDataInterface):
@@ -325,10 +351,12 @@ class Position(NWBDataInterface):
         {"from_schema": "core.nwb.behavior", "tree_root": True}
     )
 
-    value: Optional[List[SpatialSeries]] = Field(
+    name: str = Field(
+        "Position", json_schema_extra={"linkml_meta": {"ifabsent": "string(Position)"}}
+    )
+    value: Optional[Dict[str, SpatialSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpatialSeries"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_ecephys.py

@@ -190,11 +190,12 @@ class ElectricalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        NDArray[Shape["* num_times"], float],
+        None,
-        NDArray[Shape["* num_times, * num_channels"], float],
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        NDArray[Shape["* num_times, * num_channels, * num_samples"], float],
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    ] = Field(..., description="""Recorded voltage data.""")
+    )
+    data: ElectricalSeriesData = Field(..., description="""Recorded voltage data.""")
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -207,11 +208,6 @@ class ElectricalSeries(TimeSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -249,6 +245,41 @@ class ElectricalSeries(TimeSeries):
     )
 
 
+class ElectricalSeriesData(ConfiguredBaseModel):
+    """
+    Recorded voltage data.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Base unit of measurement for working with the data. This value is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion' and 'channel_conversion' (if present).""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_channels"], float | int],
+            NDArray[Shape["* num_times, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class SpikeEventSeries(ElectricalSeries):
     """
     Stores snapshots/snippets of recorded spike events (i.e., threshold crossings). This may also be raw data, as reported by ephys hardware. If so, the TimeSeries::description field should describe how events were detected. All SpikeEventSeries should reside in a module (under EventWaveform interface) even if the spikes were reported and stored by hardware. All events span the same recording channels and store snapshots of equal duration. TimeSeries::data array structure: [num events] [num channels] [num samples] (or [num events] [num samples] for single electrode).
@@ -259,15 +290,17 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: SpikeEventSeriesData = Field(..., description="""Spike waveforms.""")
-        NDArray[Shape["* num_events, * num_samples"], float],
-        NDArray[Shape["* num_events, * num_channels, * num_samples"], float],
-    ] = Field(..., description="""Spike waveforms.""")
     timestamps: NDArray[Shape["* num_times"], float] = Field(
         ...,
         description="""Timestamps for samples stored in data, in seconds, relative to the common experiment master-clock stored in NWBFile.timestamps_reference_time. Timestamps are required for the events. Unlike for TimeSeries, timestamps are required for SpikeEventSeries and are thus re-specified here.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
+    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
+        None,
+        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
+        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
+    )
     electrodes: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion pointer to the electrodes that this time series was generated from.""",
@@ -280,11 +313,6 @@ class SpikeEventSeries(ElectricalSeries):
             }
         },
     )
-    channel_conversion: Optional[NDArray[Shape["* num_channels"], float]] = Field(
-        None,
-        description="""Channel-specific conversion factor. Multiply the data in the 'data' dataset by these values along the channel axis (as indicated by axis attribute) AND by the global conversion factor in the 'conversion' attribute of 'data' to get the data values in Volts, i.e, data in Volts = data * data.conversion * channel_conversion. This approach allows for both global and per-channel data conversion factors needed to support the storage of electrical recordings as native values generated by data acquisition systems. If this dataset is not present, then there is no channel-specific conversion factor, i.e. it is 1 for all channels.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_channels"}]}}},
-    )
     description: Optional[str] = Field(
         "no description",
         description="""Description of the time series.""",
@@ -317,6 +345,40 @@ class SpikeEventSeries(ElectricalSeries):
     )
 
 
+class SpikeEventSeriesData(ConfiguredBaseModel):
+    """
+    Spike waveforms.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ecephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["volts"] = Field(
+        "volts",
+        description="""Unit of measurement for waveforms, which is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_events, * num_samples"], float | int],
+            NDArray[Shape["* num_events, * num_channels, * num_samples"], float | int],
+        ]
+    ] = Field(None)
+
+
 class FeatureExtraction(NWBDataInterface):
     """
     Features, such as PC1 and PC2, that are extracted from signals stored in a SpikeEventSeries or other source.
@@ -415,10 +477,12 @@ class EventWaveform(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[SpikeEventSeries]] = Field(
+    name: str = Field(
+        "EventWaveform", json_schema_extra={"linkml_meta": {"ifabsent": "string(EventWaveform)"}}
+    )
+    value: Optional[Dict[str, SpikeEventSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "SpikeEventSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class FilteredEphys(NWBDataInterface):
@@ -430,10 +494,12 @@ class FilteredEphys(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field(
+        "FilteredEphys", json_schema_extra={"linkml_meta": {"ifabsent": "string(FilteredEphys)"}}
+    )
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class LFP(NWBDataInterface):
@@ -445,10 +511,10 @@ class LFP(NWBDataInterface):
         {"from_schema": "core.nwb.ecephys", "tree_root": True}
     )
 
-    value: Optional[List[ElectricalSeries]] = Field(
+    name: str = Field("LFP", json_schema_extra={"linkml_meta": {"ifabsent": "string(LFP)"}})
+    value: Optional[Dict[str, ElectricalSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "ElectricalSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ElectrodeGroup(NWBContainer):
@@ -591,7 +657,9 @@ class Clustering(NWBDataInterface):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 ElectricalSeries.model_rebuild()
+ElectricalSeriesData.model_rebuild()
 SpikeEventSeries.model_rebuild()
+SpikeEventSeriesData.model_rebuild()
 FeatureExtraction.model_rebuild()
 EventDetection.model_rebuild()
 EventWaveform.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_epoch.py

@@ -247,9 +247,6 @@ class TimeIntervals(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class TimeIntervalsTimeseries(VectorData):

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_file.py

@@ -225,28 +225,28 @@ class NWBFile(NWBContainer):
         ...,
         description="""Date and time corresponding to time zero of all timestamps. The date is stored in UTC with local timezone offset as ISO 8601 extended formatted string: 2018-09-28T14:43:54.123+02:00. Dates stored in UTC end in \"Z\" with no timezone offset. Date accuracy is up to milliseconds. All times stored in the file use this time as reference (i.e., time zero).""",
     )
-    acquisition: Optional[List[Union[DynamicTable, NWBDataInterface]]] = Field(
+    acquisition: Optional[Dict[str, Union[DynamicTable, NWBDataInterface]]] = Field(
         None,
         description="""Data streams recorded from the system, including ephys, ophys, tracking, etc. This group should be read-only after the experiment is completed and timestamps are corrected to a common timebase. The data stored here may be links to raw data stored in external NWB files. This will allow keeping bulky raw data out of the file while preserving the option of keeping some/all in the file. Acquired data includes tracking and experimental data streams (i.e., everything measured from the system). If bulky data is stored in the /acquisition group, the data can exist in a separate NWB file that is linked to by the file being used for processing and analysis.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBDataInterface"}, {"range": "DynamicTable"}]}
         },
     )
-    analysis: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    analysis: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""Lab-specific and custom scientific analysis of data. There is no defined format for the content of this group - the format is up to the individual user/lab. To facilitate sharing analysis data between labs, the contents here should be stored in standard types (e.g., neurodata_types) and appropriately documented. The file can store lab-specific and custom data analysis without restriction on its form or schema, reducing data formatting restrictions on end users. Such data should be placed in the analysis group. The analysis data should be documented so that it could be shared with other labs.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    scratch: Optional[List[Union[DynamicTable, NWBContainer]]] = Field(
+    scratch: Optional[Dict[str, Union[DynamicTable, NWBContainer]]] = Field(
         None,
         description="""A place to store one-off analysis results. Data placed here is not intended for sharing. By placing data here, users acknowledge that there is no guarantee that their data meets any standard.""",
         json_schema_extra={
             "linkml_meta": {"any_of": [{"range": "NWBContainer"}, {"range": "DynamicTable"}]}
         },
     )
-    processing: Optional[List[ProcessingModule]] = Field(
+    processing: Optional[Dict[str, ProcessingModule]] = Field(
         None,
         description="""The home for ProcessingModules. These modules perform intermediate analysis of data that is necessary to perform before scientific analysis. Examples include spike clustering, extracting position from tracking data, stitching together image slices. ProcessingModules can be large and express many data sets from relatively complex analysis (e.g., spike detection and clustering) or small, representing extraction of position information from tracking video, or even binary lick/no-lick decisions. Common software tools (e.g., klustakwik, MClust) are expected to read/write data here.  'Processing' refers to intermediate analysis of the acquired data to make it more amenable to scientific analysis.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ProcessingModule"}]}},
@@ -264,6 +264,9 @@ class NWBFile(NWBContainer):
         description="""Experimental intervals, whether that be logically distinct sub-experiments having a particular scientific goal, trials (see trials subgroup) during an experiment, or epochs (see epochs subgroup) deriving from analysis of data.""",
     )
     units: Optional[Units] = Field(None, description="""Data about sorted spike units.""")
+    specifications: Optional[dict] = Field(
+        None, description="""Nested dictionary of schema specifications"""
+    )
 
 
 class NWBFileStimulus(ConfiguredBaseModel):
@@ -279,12 +282,12 @@ class NWBFileStimulus(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "stimulus", "ifabsent": "string(stimulus)"}
         },
     )
-    presentation: Optional[List[TimeSeries]] = Field(
+    presentation: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Stimuli presented during the experiment.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
     )
-    templates: Optional[List[TimeSeries]] = Field(
+    templates: Optional[Dict[str, TimeSeries]] = Field(
         None,
         description="""Template stimuli. Timestamps in templates are based on stimulus design and are relative to the beginning of the stimulus. When templates are used, the stimulus instances must convert presentation times to the experiment`s time reference frame.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "TimeSeries"}]}},
@@ -362,11 +365,7 @@ class NWBFileGeneral(ConfiguredBaseModel):
         None,
         description="""Information about virus(es) used in experiments, including virus ID, source, date made, injection location, volume, etc.""",
     )
-    lab_meta_data: Optional[List[LabMetaData]] = Field(
+    devices: Optional[Dict[str, Device]] = Field(
-        None,
-        description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
-    )
-    devices: Optional[List[Device]] = Field(
         None,
         description="""Description of hardware devices used during experiment, e.g., monitors, ADC boards, microscopes, etc.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "Device"}]}},
@@ -381,16 +380,20 @@ class NWBFileGeneral(ConfiguredBaseModel):
     intracellular_ephys: Optional[GeneralIntracellularEphys] = Field(
         None, description="""Metadata related to intracellular electrophysiology."""
     )
-    optogenetics: Optional[List[OptogeneticStimulusSite]] = Field(
+    optogenetics: Optional[Dict[str, OptogeneticStimulusSite]] = Field(
         None,
         description="""Metadata describing optogenetic stimuluation.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "OptogeneticStimulusSite"}]}},
     )
-    optophysiology: Optional[List[ImagingPlane]] = Field(
+    optophysiology: Optional[Dict[str, ImagingPlane]] = Field(
         None,
         description="""Metadata related to optophysiology.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImagingPlane"}]}},
     )
+    value: Optional[Dict[str, LabMetaData]] = Field(
+        None,
+        description="""Place-holder than can be extended so that lab-specific meta-data can be placed in /general.""",
+    )
 
 
 class GeneralSourceScript(ConfiguredBaseModel):
@@ -426,12 +429,12 @@ class GeneralExtracellularEphys(ConfiguredBaseModel):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
-        None, description="""Physical group of electrodes."""
-    )
     electrodes: Optional[ExtracellularEphysElectrodes] = Field(
         None, description="""A table of all electrodes (i.e. channels) used for recording."""
     )
+    value: Optional[Dict[str, ElectrodeGroup]] = Field(
+        None, description="""Physical group of electrodes."""
+    )
 
 
 class ExtracellularEphysElectrodes(DynamicTable):
@@ -501,8 +504,14 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    group: List[ElectrodeGroup] = Field(
+    group: VectorData[NDArray[Any, ElectrodeGroup]] = Field(
-        ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
+        ...,
+        description="""Reference to the ElectrodeGroup this electrode is a part of.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
     )
     group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
@@ -559,9 +568,6 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class GeneralIntracellularEphys(ConfiguredBaseModel):
@@ -584,12 +590,12 @@ class GeneralIntracellularEphys(ConfiguredBaseModel):
         None,
         description="""Description of filtering used. Includes filtering type and parameters, frequency fall-off, etc. If this changes between TimeSeries, filter description should be stored as a text attribute for each TimeSeries.""",
     )
-    intracellular_electrode: Optional[List[IntracellularElectrode]] = Field(
-        None, description="""An intracellular electrode."""
-    )
     sweep_table: Optional[SweepTable] = Field(
         None, description="""The table which groups different PatchClampSeries together."""
     )
+    value: Optional[Dict[str, IntracellularElectrode]] = Field(
+        None, description="""An intracellular electrode."""
+    )
 
 
 class NWBFileIntervals(ConfiguredBaseModel):
@@ -615,7 +621,7 @@ class NWBFileIntervals(ConfiguredBaseModel):
     invalid_times: Optional[TimeIntervals] = Field(
         None, description="""Time intervals that should be removed from analysis."""
     )
-    time_intervals: Optional[List[TimeIntervals]] = Field(
+    value: Optional[Dict[str, TimeIntervals]] = Field(
         None,
         description="""Optional additional table(s) for describing other experimental time intervals.""",
     )

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_icephys.py

@@ -262,11 +262,21 @@ class PatchClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         ...,
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
     )
-    value: Optional[NDArray[Shape["* num_times"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
         None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
     )
 
@@ -281,12 +291,12 @@ class CurrentClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     bias_current: Optional[float] = Field(None, description="""Bias current, in amps.""")
     bridge_balance: Optional[float] = Field(None, description="""Bridge balance, in ohms.""")
     capacitance_compensation: Optional[float] = Field(
         None, description="""Capacitance compensation, in farads."""
     )
+    data: CurrentClampSeriesData = Field(..., description="""Recorded voltage.""")
     stimulus_description: str = Field(
         ..., description="""Protocol/stimulus name for this patch-clamp dataset."""
     )
@@ -354,12 +364,24 @@ class CurrentClampSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IZeroClampSeries(CurrentClampSeries):
@@ -512,6 +534,16 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["amperes"] = Field(
         "amperes",
         description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
@@ -519,7 +551,9 @@ class CurrentClampStimulusSeriesData(ConfiguredBaseModel):
             "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
         },
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class VoltageClampSeries(PatchClampSeries):
@@ -532,13 +566,13 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
     name: str = Field(...)
-    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     capacitance_fast: Optional[VoltageClampSeriesCapacitanceFast] = Field(
         None, description="""Fast capacitance, in farads."""
     )
     capacitance_slow: Optional[VoltageClampSeriesCapacitanceSlow] = Field(
         None, description="""Slow capacitance, in farads."""
     )
+    data: VoltageClampSeriesData = Field(..., description="""Recorded current.""")
     resistance_comp_bandwidth: Optional[VoltageClampSeriesResistanceCompBandwidth] = Field(
         None, description="""Resistance compensation bandwidth, in hertz."""
     )
@@ -610,27 +644,6 @@ class VoltageClampSeries(PatchClampSeries):
     )
 
 
-class VoltageClampSeriesData(ConfiguredBaseModel):
-    """
-    Recorded current.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
-
-    name: Literal["data"] = Field(
-        "data",
-        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
-    )
-    unit: Literal["amperes"] = Field(
-        "amperes",
-        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
-        },
-    )
-    value: Any = Field(...)
-
-
 class VoltageClampSeriesCapacitanceFast(ConfiguredBaseModel):
     """
     Fast capacitance, in farads.
@@ -683,6 +696,39 @@ class VoltageClampSeriesCapacitanceSlow(ConfiguredBaseModel):
     value: float = Field(...)
 
 
+class VoltageClampSeriesData(ConfiguredBaseModel):
+    """
+    Recorded current.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.icephys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["amperes"] = Field(
+        "amperes",
+        description="""Base unit of measurement for working with the data. which is fixed to 'amperes'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "amperes", "ifabsent": "string(amperes)"}
+        },
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class VoltageClampSeriesResistanceCompBandwidth(ConfiguredBaseModel):
     """
     Resistance compensation bandwidth, in hertz.
@@ -887,12 +933,24 @@ class VoltageClampStimulusSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Literal["volts"] = Field(
         "volts",
         description="""Base unit of measurement for working with the data. which is fixed to 'volts'. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
     )
-    value: Any = Field(...)
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
 
 
 class IntracellularElectrode(NWBContainer):
@@ -942,18 +1000,15 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: VectorData[NDArray[Any, int]] = Field(
+    series: VectorData[NDArray[Any, PatchClampSeries]] = Field(
         ...,
-        description="""Sweep number of the PatchClampSeries in that row.""",
+        description="""The PatchClampSeries with the sweep number in that row.""",
         json_schema_extra={
             "linkml_meta": {
                 "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
             }
         },
     )
-    series: List[PatchClampSeries] = Field(
-        ..., description="""The PatchClampSeries with the sweep number in that row."""
-    )
     series_index: Named[VectorIndex] = Field(
         ...,
         description="""Index for series.""",
@@ -966,6 +1021,15 @@ class SweepTable(DynamicTable):
             }
         },
     )
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
+        ...,
+        description="""Sweep number of the PatchClampSeries in that row.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -976,9 +1040,6 @@ class SweepTable(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild
@@ -991,9 +1052,9 @@ IZeroClampSeries.model_rebuild()
 CurrentClampStimulusSeries.model_rebuild()
 CurrentClampStimulusSeriesData.model_rebuild()
 VoltageClampSeries.model_rebuild()
-VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesCapacitanceFast.model_rebuild()
 VoltageClampSeriesCapacitanceSlow.model_rebuild()
+VoltageClampSeriesData.model_rebuild()
 VoltageClampSeriesResistanceCompBandwidth.model_rebuild()
 VoltageClampSeriesResistanceCompCorrection.model_rebuild()
 VoltageClampSeriesResistanceCompPrediction.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_image.py

@@ -152,7 +152,7 @@ class GrayscaleImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {"array": {"dimensions": [{"alias": "x"}, {"alias": "y"}]}}
@@ -174,7 +174,7 @@ class RGBImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 3 r_g_b"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -204,7 +204,7 @@ class RGBAImage(Image):
     )
 
     name: str = Field(...)
-    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float]] = Field(
+    value: Optional[NDArray[Shape["* x, * y, 4 r_g_b_a"], float | int]] = Field(
         None,
         json_schema_extra={
             "linkml_meta": {
@@ -234,12 +234,9 @@ class ImageSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -250,8 +247,9 @@ class ImageSeries(TimeSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -290,6 +288,39 @@ class ImageSeries(TimeSeries):
     )
 
 
+class ImageSeriesData(ConfiguredBaseModel):
+    """
+    Binary data representing images across frames.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, * z"], float | int],
+        ]
+    ] = Field(None)
+
+
 class ImageSeriesExternalFile(ConfiguredBaseModel):
     """
     Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.
@@ -331,12 +362,9 @@ class ImageMaskSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -347,8 +375,9 @@ class ImageMaskSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -397,6 +426,9 @@ class OpticalSeries(ImageSeries):
     )
 
     name: str = Field(...)
+    data: OpticalSeriesData = Field(
+        ..., description="""Images presented to subject, either grayscale or RGB"""
+    )
     distance: Optional[float] = Field(
         None, description="""Distance from camera/monitor to target/eye."""
     )
@@ -405,10 +437,6 @@ class OpticalSeries(ImageSeries):
             NDArray[Shape["2 width_height"], float], NDArray[Shape["3 width_height_depth"], float]
         ]
     ] = Field(None, description="""Width, height and depth of image, or imaged area, in meters.""")
-    data: Union[
-        NDArray[Shape["* frame, * x, * y"], float],
-        NDArray[Shape["* frame, * x, * y, 3 r_g_b"], float],
-    ] = Field(..., description="""Images presented to subject, either grayscale or RGB""")
     orientation: Optional[str] = Field(
         None,
         description="""Description of image relative to some reference frame (e.g., which way is up). Must also specify frame of reference.""",
@@ -423,8 +451,9 @@ class OpticalSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -463,6 +492,39 @@ class OpticalSeries(ImageSeries):
     )
 
 
+class OpticalSeriesData(ConfiguredBaseModel):
+    """
+    Images presented to subject, either grayscale or RGB
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* frame, * x, * y"], float | int],
+            NDArray[Shape["* frame, * x, * y, 3 r_g_b"], float | int],
+        ]
+    ] = Field(None)
+
+
 class IndexSeries(TimeSeries):
     """
     Stores indices to image frames stored in an ImageSeries. The purpose of the ImageIndexSeries is to allow a static image stack to be stored somewhere, and the images in the stack to be referenced out-of-order. This can be for the display of individual images, or of movie segments (as a movie is simply a series of images). The data field stores the index of the frame in the referenced ImageSeries, and the timestamps array indicates when that image was displayed.
@@ -473,10 +535,8 @@ class IndexSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IndexSeriesData = Field(
-        ...,
+        ..., description="""Index of the frame in the referenced ImageSeries."""
-        description="""Index of the frame in the referenced ImageSeries.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     indexed_timeseries: Union[ImageSeries, str] = Field(
         ...,
@@ -524,13 +584,46 @@ class IndexSeries(TimeSeries):
     )
 
 
+class IndexSeriesData(ConfiguredBaseModel):
+    """
+    Index of the frame in the referenced ImageSeries.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.image"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 GrayscaleImage.model_rebuild()
 RGBImage.model_rebuild()
 RGBAImage.model_rebuild()
 ImageSeries.model_rebuild()
+ImageSeriesData.model_rebuild()
 ImageSeriesExternalFile.model_rebuild()
 ImageMaskSeries.model_rebuild()
 OpticalSeries.model_rebuild()
+OpticalSeriesData.model_rebuild()
 IndexSeries.model_rebuild()
+IndexSeriesData.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_misc.py

@@ -251,6 +251,16 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: Optional[str] = Field(
         "see ",
         description="""Since there can be different units for different features, store the units in 'feature_units'. The default value for this attribute is \"see 'feature_units'\".""",
@@ -258,8 +268,8 @@ class AbstractFeatureSeriesData(ConfiguredBaseModel):
     )
     value: Optional[
         Union[
-            NDArray[Shape["* num_times"], float],
+            NDArray[Shape["* num_times"], float | int],
-            NDArray[Shape["* num_times, * num_features"], float],
+            NDArray[Shape["* num_times, * num_features"], float | int],
         ]
     ] = Field(None)
 
@@ -274,10 +284,8 @@ class AnnotationSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], str] = Field(
+    data: AnnotationSeriesData = Field(
-        ...,
+        ..., description="""Annotations made during an experiment."""
-        description="""Annotations made during an experiment.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -316,6 +324,39 @@ class AnnotationSeries(TimeSeries):
     )
 
 
+class AnnotationSeriesData(ConfiguredBaseModel):
+    """
+    Annotations made during an experiment.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], str]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class IntervalSeries(TimeSeries):
     """
     Stores intervals of data. The timestamps field stores the beginning and end of intervals. The data field stores whether the interval just started (>0 value) or ended (<0 value). Different interval types can be represented in the same series by using multiple key values (eg, 1 for feature A, 2 for feature B, 3 for feature C, etc). The field data stores an 8-bit integer. This is largely an alias of a standard TimeSeries but that is identifiable as representing time intervals in a machine-readable way.
@@ -326,10 +367,8 @@ class IntervalSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], int] = Field(
+    data: IntervalSeriesData = Field(
-        ...,
+        ..., description="""Use values >0 if interval started, <0 if interval ended."""
-        description="""Use values >0 if interval started, <0 if interval ended.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -368,6 +407,39 @@ class IntervalSeries(TimeSeries):
     )
 
 
+class IntervalSeriesData(ConfiguredBaseModel):
+    """
+    Use values >0 if interval started, <0 if interval ended.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: float = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data. Annotations have no units, so the value is fixed to -1.0.""",
+        le=-1,
+        ge=-1,
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["n/a"] = Field(
+        "n/a",
+        description="""Base unit of measurement for working with the data. Annotations have no units, so the value is fixed to 'n/a'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "n/a", "ifabsent": "string(n/a)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class DecompositionSeries(TimeSeries):
     """
     Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -443,24 +515,36 @@ class DecompositionSeriesData(ConfiguredBaseModel):
         "data",
         json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
     unit: str = Field(
         "no unit",
         description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
         json_schema_extra={"linkml_meta": {"ifabsent": "string(no unit)"}},
     )
-    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float]] = Field(
+    value: Optional[NDArray[Shape["* num_times, * num_channels, * num_bands"], float | int]] = (
-        None,
+        Field(
-        json_schema_extra={
+            None,
-            "linkml_meta": {
+            json_schema_extra={
-                "array": {
+                "linkml_meta": {
-                    "dimensions": [
+                    "array": {
-                        {"alias": "num_times"},
+                        "dimensions": [
-                        {"alias": "num_channels"},
+                            {"alias": "num_times"},
-                        {"alias": "num_bands"},
+                            {"alias": "num_channels"},
-                    ]
+                            {"alias": "num_bands"},
+                        ]
+                    }
                 }
-            }
+            },
-        },
+        )
     )
 
 
@@ -518,9 +602,6 @@ class DecompositionSeriesBands(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class Units(DynamicTable):
@@ -533,9 +614,18 @@ class Units(DynamicTable):
     )
 
     name: str = Field("Units", json_schema_extra={"linkml_meta": {"ifabsent": "string(Units)"}})
-    spike_times_index: Optional[Named[VectorIndex]] = Field(
+    electrode_group: Optional[VectorData[NDArray[Any, ElectrodeGroup]]] = Field(
         None,
-        description="""Index into the spike_times dataset.""",
+        description="""Electrode group that each spike unit came from.""",
+        json_schema_extra={
+            "linkml_meta": {
+                "array": {"maximum_number_dimensions": False, "minimum_number_dimensions": 1}
+            }
+        },
+    )
+    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+        None,
+        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -545,12 +635,9 @@ class Units(DynamicTable):
             }
         },
     )
-    spike_times: Optional[UnitsSpikeTimes] = Field(
+    electrodes_index: Optional[Named[VectorIndex]] = Field(
-        None, description="""Spike times for each unit."""
-    )
-    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into the obs_intervals dataset.""",
+        description="""Index into electrodes.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -576,9 +663,9 @@ class Units(DynamicTable):
             },
         )
     )
-    electrodes_index: Optional[Named[VectorIndex]] = Field(
+    obs_intervals_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Index into electrodes.""",
+        description="""Index into the obs_intervals dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -588,9 +675,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrodes: Optional[Named[DynamicTableRegion]] = Field(
+    spike_times: Optional[UnitsSpikeTimes] = Field(
+        None, description="""Spike times for each unit."""
+    )
+    spike_times_index: Optional[Named[VectorIndex]] = Field(
         None,
-        description="""Electrode that each spike unit came from, specified using a DynamicTableRegion.""",
+        description="""Index into the spike_times dataset.""",
         json_schema_extra={
             "linkml_meta": {
                 "annotations": {
@@ -600,25 +690,12 @@ class Units(DynamicTable):
             }
         },
     )
-    electrode_group: Optional[List[ElectrodeGroup]] = Field(
+    waveform_mean: Optional[UnitsWaveformMean] = Field(
-        None, description="""Electrode group that each spike unit came from."""
+        None, description="""Spike waveform mean for each spike unit."""
+    )
+    waveform_sd: Optional[UnitsWaveformSd] = Field(
+        None, description="""Spike waveform standard deviation for each spike unit."""
     )
-    waveform_mean: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        VectorData[
-            Union[
-                NDArray[Shape["* num_units, * num_samples"], float],
-                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
-            ]
-        ]
-    ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
@@ -629,9 +706,6 @@ class Units(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 class UnitsSpikeTimes(VectorData):
@@ -662,14 +736,78 @@ class UnitsSpikeTimes(VectorData):
     ] = Field(None)
 
 
+class UnitsWaveformMean(VectorData):
+    """
+    Spike waveform mean for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_mean"] = Field(
+        "waveform_mean",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_mean", "ifabsent": "string(waveform_mean)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+    value: Optional[
+        Union[
+            NDArray[Shape["* dim0"], Any],
+            NDArray[Shape["* dim0, * dim1"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
+        ]
+    ] = Field(None)
+
+
+class UnitsWaveformSd(VectorData):
+    """
+    Spike waveform standard deviation for each spike unit.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.misc"})
+
+    name: Literal["waveform_sd"] = Field(
+        "waveform_sd",
+        json_schema_extra={
+            "linkml_meta": {"equals_string": "waveform_sd", "ifabsent": "string(waveform_sd)"}
+        },
+    )
+    sampling_rate: Optional[float] = Field(None, description="""Sampling rate, in hertz.""")
+    unit: Optional[Literal["volts"]] = Field(
+        "volts",
+        description="""Unit of measurement. This value is fixed to 'volts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "volts", "ifabsent": "string(volts)"}},
+    )
+    description: str = Field(..., description="""Description of what these vectors represent.""")
+    value: Optional[
+        Union[
+            NDArray[Shape["* dim0"], Any],
+            NDArray[Shape["* dim0, * dim1"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
+            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
+        ]
+    ] = Field(None)
+
+
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 AbstractFeatureSeries.model_rebuild()
 AbstractFeatureSeriesData.model_rebuild()
 AnnotationSeries.model_rebuild()
+AnnotationSeriesData.model_rebuild()
 IntervalSeries.model_rebuild()
+IntervalSeriesData.model_rebuild()
 DecompositionSeries.model_rebuild()
 DecompositionSeriesData.model_rebuild()
 DecompositionSeriesBands.model_rebuild()
 Units.model_rebuild()
 UnitsSpikeTimes.model_rebuild()
+UnitsWaveformMean.model_rebuild()
+UnitsWaveformSd.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_ogen.py

@@ -158,10 +158,8 @@ class OptogeneticSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: NDArray[Shape["* num_times"], float] = Field(
+    data: OptogeneticSeriesData = Field(
-        ...,
+        ..., description="""Applied power for optogenetic stimulus, in watts."""
-        description="""Applied power for optogenetic stimulus, in watts.""",
-        json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}},
     )
     site: Union[OptogeneticStimulusSite, str] = Field(
         ...,
@@ -209,6 +207,37 @@ class OptogeneticSeries(TimeSeries):
     )
 
 
+class OptogeneticSeriesData(ConfiguredBaseModel):
+    """
+    Applied power for optogenetic stimulus, in watts.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ogen"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: Literal["watts"] = Field(
+        "watts",
+        description="""Unit of measurement for data, which is fixed to 'watts'.""",
+        json_schema_extra={"linkml_meta": {"equals_string": "watts", "ifabsent": "string(watts)"}},
+    )
+    value: Optional[NDArray[Shape["* num_times"], float | int]] = Field(
+        None, json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_times"}]}}}
+    )
+
+
 class OptogeneticStimulusSite(NWBContainer):
     """
     A site of optogenetic stimulation.
@@ -239,4 +268,5 @@ class OptogeneticStimulusSite(NWBContainer):
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 OptogeneticSeries.model_rebuild()
+OptogeneticSeriesData.model_rebuild()
 OptogeneticStimulusSite.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/core_nwb_ophys.py

@@ -28,7 +28,7 @@ from ...core.v2_2_5.core_nwb_base import (
     TimeSeriesSync,
 )
 from ...core.v2_2_5.core_nwb_device import Device
-from ...core.v2_2_5.core_nwb_image import ImageSeries, ImageSeriesExternalFile
+from ...core.v2_2_5.core_nwb_image import ImageSeries, ImageSeriesData, ImageSeriesExternalFile
 from ...hdmf_common.v1_1_3.hdmf_common_table import (
     DynamicTable,
     DynamicTableRegion,
@@ -217,12 +217,9 @@ class TwoPhotonSeries(ImageSeries):
             }
         },
     )
-    data: Optional[
+    data: Optional[ImageSeriesData] = Field(
-        Union[
+        None, description="""Binary data representing images across frames."""
-            NDArray[Shape["* frame, * x, * y"], float],
+    )
-            NDArray[Shape["* frame, * x, * y, * z"], float],
-        ]
-    ] = Field(None, description="""Binary data representing images across frames.""")
     dimension: Optional[NDArray[Shape["* rank"], int]] = Field(
         None,
         description="""Number of pixels on x, y, (and z) axes.""",
@@ -233,8 +230,9 @@ class TwoPhotonSeries(ImageSeries):
         description="""Paths to one or more external file(s). The field is only present if format='external'. This is only relevant if the image series is stored in the file system as one or more image file(s). This field should NOT be used if the image is stored in another NWB file and that file is linked to this file.""",
     )
     format: Optional[str] = Field(
-        None,
+        "raw",
         description="""Format of image. If this is 'external', then the attribute 'external_file' contains the path information to the image files. If this is 'raw', then the raw (single-channel) binary data is stored in the 'data' dataset. If this attribute is not present, then the default format='raw' case is assumed.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(raw)"}},
     )
     description: Optional[str] = Field(
         "no description",
@@ -283,9 +281,7 @@ class RoiResponseSeries(TimeSeries):
     )
 
     name: str = Field(...)
-    data: Union[
+    data: RoiResponseSeriesData = Field(..., description="""Signals from ROIs.""")
-        NDArray[Shape["* num_times"], float], NDArray[Shape["* num_times, * num_rois"], float]
-    ] = Field(..., description="""Signals from ROIs.""")
     rois: Named[DynamicTableRegion] = Field(
         ...,
         description="""DynamicTableRegion referencing into an ROITable containing information on the ROIs stored in this timeseries.""",
@@ -335,6 +331,39 @@ class RoiResponseSeries(TimeSeries):
     )
 
 
+class RoiResponseSeriesData(ConfiguredBaseModel):
+    """
+    Signals from ROIs.
+    """
+
+    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
+
+    name: Literal["data"] = Field(
+        "data",
+        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
+    )
+    conversion: Optional[float] = Field(
+        1.0,
+        description="""Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(1.0)"}},
+    )
+    resolution: Optional[float] = Field(
+        -1.0,
+        description="""Smallest meaningful difference between values in data, stored in the specified by unit, e.g., the change in value of the least significant bit, or a larger number if signal noise is known to be present. If unknown, use -1.0.""",
+        json_schema_extra={"linkml_meta": {"ifabsent": "float(-1.0)"}},
+    )
+    unit: str = Field(
+        ...,
+        description="""Base unit of measurement for working with the data. Actual stored values are not necessarily stored in these units. To access the data in these units, multiply 'data' by 'conversion'.""",
+    )
+    value: Optional[
+        Union[
+            NDArray[Shape["* num_times"], float | int],
+            NDArray[Shape["* num_times, * num_rois"], float | int],
+        ]
+    ] = Field(None)
+
+
 class DfOverF(NWBDataInterface):
     """
     dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (i.e., same names for ROIs and for image planes).
@@ -344,10 +373,10 @@ class DfOverF(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field("DfOverF", json_schema_extra={"linkml_meta": {"ifabsent": "string(DfOverF)"}})
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class Fluorescence(NWBDataInterface):
@@ -359,10 +388,12 @@ class Fluorescence(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[RoiResponseSeries]] = Field(
+    name: str = Field(
+        "Fluorescence", json_schema_extra={"linkml_meta": {"ifabsent": "string(Fluorescence)"}}
+    )
+    value: Optional[Dict[str, RoiResponseSeries]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "RoiResponseSeries"}]}}
     )
-    name: str = Field(...)
 
 
 class ImageSegmentation(NWBDataInterface):
@@ -374,10 +405,13 @@ class ImageSegmentation(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[PlaneSegmentation]] = Field(
+    name: str = Field(
+        "ImageSegmentation",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(ImageSegmentation)"}},
+    )
+    value: Optional[Dict[str, PlaneSegmentation]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "PlaneSegmentation"}]}}
     )
-    name: str = Field(...)
 
 
 class PlaneSegmentation(DynamicTable):
@@ -390,10 +424,21 @@ class PlaneSegmentation(DynamicTable):
     )
 
     name: str = Field(...)
-    image_mask: Optional[PlaneSegmentationImageMask] = Field(
+    image_mask: Optional[
+        VectorData[
+            Union[
+                NDArray[Shape["* num_roi, * num_x, * num_y"], Any],
+                NDArray[Shape["* num_roi, * num_x, * num_y, * num_z"], Any],
+            ]
+        ]
+    ] = Field(
         None,
         description="""ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero.""",
     )
+    pixel_mask: Optional[PlaneSegmentationPixelMask] = Field(
+        None,
+        description="""Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
+    )
     pixel_mask_index: Optional[Named[VectorIndex]] = Field(
         None,
         description="""Index into pixel_mask.""",
@@ -406,9 +451,9 @@ class PlaneSegmentation(DynamicTable):
             }
         },
     )
-    pixel_mask: Optional[PlaneSegmentationPixelMask] = Field(
+    voxel_mask: Optional[PlaneSegmentationVoxelMask] = Field(
         None,
-        description="""Pixel masks for each ROI: a list of indices and weights for the ROI. Pixel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
+        description="""Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
     )
     voxel_mask_index: Optional[Named[VectorIndex]] = Field(
         None,
@@ -422,11 +467,7 @@ class PlaneSegmentation(DynamicTable):
             }
         },
     )
-    voxel_mask: Optional[PlaneSegmentationVoxelMask] = Field(
+    reference_images: Optional[Dict[str, ImageSeries]] = Field(
-        None,
-        description="""Voxel masks for each ROI: a list of indices and weights for the ROI. Voxel masks are concatenated and parsing of this dataset is maintained by the PlaneSegmentation""",
-    )
-    reference_images: Optional[List[ImageSeries]] = Field(
         None,
         description="""Image stacks that the segmentation masks apply to.""",
         json_schema_extra={"linkml_meta": {"any_of": [{"range": "ImageSeries"}]}},
@@ -450,33 +491,6 @@ class PlaneSegmentation(DynamicTable):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
-
-
-class PlaneSegmentationImageMask(VectorData):
-    """
-    ROI masks for each ROI. Each image mask is the size of the original imaging plane (or volume) and members of the ROI are finite non-zero.
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "core.nwb.ophys"})
-
-    name: Literal["image_mask"] = Field(
-        "image_mask",
-        json_schema_extra={
-            "linkml_meta": {"equals_string": "image_mask", "ifabsent": "string(image_mask)"}
-        },
-    )
-    description: str = Field(..., description="""Description of what these vectors represent.""")
-    value: Optional[
-        Union[
-            NDArray[Shape["* dim0"], Any],
-            NDArray[Shape["* dim0, * dim1"], Any],
-            NDArray[Shape["* dim0, * dim1, * dim2"], Any],
-            NDArray[Shape["* dim0, * dim1, * dim2, * dim3"], Any],
-        ]
-    ] = Field(None)
 
 
 class PlaneSegmentationPixelMask(VectorData):
@@ -599,7 +613,7 @@ class ImagingPlane(NWBContainer):
         None,
         description="""Describes reference frame of origin_coords and grid_spacing. For example, this can be a text description of the anatomical location and orientation of the grid defined by origin_coords and grid_spacing or the vectors needed to transform or rotate the grid to a common anatomical axis (e.g., AP/DV/ML). This field is necessary to interpret origin_coords and grid_spacing. If origin_coords and grid_spacing are not present, then this field is not required. For example, if the microscope takes 10 x 10 x 2 images, where the first value of the data matrix (index (0, 0, 0)) corresponds to (-1.2, -0.6, -2) mm relative to bregma, the spacing between pixels is 0.2 mm in x, 0.2 mm in y and 0.5 mm in z, and larger numbers in x means more anterior, larger numbers in y means more rightward, and larger numbers in z means more ventral, then enter the following -- origin_coords = (-1.2, -0.6, -2) grid_spacing = (0.2, 0.2, 0.5) reference_frame = \"Origin coordinates are relative to bregma. First dimension corresponds to anterior-posterior axis (larger index = more anterior). Second dimension corresponds to medial-lateral axis (larger index = more rightward). Third dimension corresponds to dorsal-ventral axis (larger index = more ventral).\"""",
     )
-    optical_channel: List[OpticalChannel] = Field(
+    optical_channel: Dict[str, OpticalChannel] = Field(
         ..., description="""An optical channel used to record from an imaging plane."""
     )
     device: Union[Device, str] = Field(
@@ -713,10 +727,13 @@ class MotionCorrection(NWBDataInterface):
         {"from_schema": "core.nwb.ophys", "tree_root": True}
     )
 
-    value: Optional[List[CorrectedImageStack]] = Field(
+    name: str = Field(
+        "MotionCorrection",
+        json_schema_extra={"linkml_meta": {"ifabsent": "string(MotionCorrection)"}},
+    )
+    value: Optional[Dict[str, CorrectedImageStack]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "CorrectedImageStack"}]}}
     )
-    name: str = Field(...)
 
 
 class CorrectedImageStack(NWBDataInterface):
@@ -751,11 +768,11 @@ class CorrectedImageStack(NWBDataInterface):
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 TwoPhotonSeries.model_rebuild()
 RoiResponseSeries.model_rebuild()
+RoiResponseSeriesData.model_rebuild()
 DfOverF.model_rebuild()
 Fluorescence.model_rebuild()
 ImageSegmentation.model_rebuild()
 PlaneSegmentation.model_rebuild()
-PlaneSegmentationImageMask.model_rebuild()
 PlaneSegmentationPixelMask.model_rebuild()
 PlaneSegmentationVoxelMask.model_rebuild()
 ImagingPlane.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/core/v2_2_5/namespace.py

@@ -38,6 +38,7 @@ from ...core.v2_2_5.core_nwb_ecephys import (
     ClusterWaveforms,
     Clustering,
     ElectricalSeries,
+    ElectricalSeriesData,
     ElectrodeGroup,
     ElectrodeGroupPosition,
     EventDetection,
@@ -46,6 +47,7 @@ from ...core.v2_2_5.core_nwb_ecephys import (
     FilteredEphys,
     LFP,
     SpikeEventSeries,
+    SpikeEventSeriesData,
 )
 from ...core.v2_2_5.core_nwb_epoch import TimeIntervals, TimeIntervalsTimeseries
 from ...core.v2_2_5.core_nwb_file import (
@@ -87,9 +89,12 @@ from ...core.v2_2_5.core_nwb_image import (
     GrayscaleImage,
     ImageMaskSeries,
     ImageSeries,
+    ImageSeriesData,
     ImageSeriesExternalFile,
     IndexSeries,
+    IndexSeriesData,
     OpticalSeries,
+    OpticalSeriesData,
     RGBAImage,
     RGBImage,
 )
@@ -97,14 +102,22 @@ from ...core.v2_2_5.core_nwb_misc import (
     AbstractFeatureSeries,
     AbstractFeatureSeriesData,
     AnnotationSeries,
+    AnnotationSeriesData,
     DecompositionSeries,
     DecompositionSeriesBands,
     DecompositionSeriesData,
     IntervalSeries,
+    IntervalSeriesData,
     Units,
     UnitsSpikeTimes,
+    UnitsWaveformMean,
+    UnitsWaveformSd,
+)
+from ...core.v2_2_5.core_nwb_ogen import (
+    OptogeneticSeries,
+    OptogeneticSeriesData,
+    OptogeneticStimulusSite,
 )
-from ...core.v2_2_5.core_nwb_ogen import OptogeneticSeries, OptogeneticStimulusSite
 from ...core.v2_2_5.core_nwb_ophys import (
     CorrectedImageStack,
     DfOverF,
@@ -117,10 +130,10 @@ from ...core.v2_2_5.core_nwb_ophys import (
     MotionCorrection,
     OpticalChannel,
     PlaneSegmentation,
-    PlaneSegmentationImageMask,
     PlaneSegmentationPixelMask,
     PlaneSegmentationVoxelMask,
     RoiResponseSeries,
+    RoiResponseSeriesData,
     TwoPhotonSeries,
 )
 from ...core.v2_2_5.core_nwb_retinotopy import (

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_1_0/hdmf_common_table.py

@@ -989,12 +989,12 @@ class DynamicTableRegion(DynamicTableRegionMixin, VectorData):
     )
 
     name: str = Field(...)
-    table: DynamicTable = Field(
-        ..., description="""Reference to the DynamicTable object that this region applies to."""
-    )
     description: str = Field(
         ..., description="""Description of what this table region points to."""
     )
+    table: DynamicTable = Field(
+        ..., description="""Reference to the DynamicTable object that this region applies to."""
+    )
 
 
 class Container(ConfiguredBaseModel):
@@ -1029,9 +1029,6 @@ class DynamicTable(DynamicTableMixin):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_1_2/hdmf_common_table.py

@@ -989,12 +989,12 @@ class DynamicTableRegion(DynamicTableRegionMixin, VectorData):
     )
 
     name: str = Field(...)
-    table: DynamicTable = Field(
-        ..., description="""Reference to the DynamicTable object that this region applies to."""
-    )
     description: str = Field(
         ..., description="""Description of what this table region points to."""
     )
+    table: DynamicTable = Field(
+        ..., description="""Reference to the DynamicTable object that this region applies to."""
+    )
 
 
 class Container(ConfiguredBaseModel):
@@ -1029,9 +1029,6 @@ class DynamicTable(DynamicTableMixin):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_1_3/hdmf_common_table.py

@@ -993,12 +993,12 @@ class DynamicTableRegion(DynamicTableRegionMixin, VectorData):
     )
 
     name: str = Field(...)
-    table: DynamicTable = Field(
-        ..., description="""Reference to the DynamicTable object that this region applies to."""
-    )
     description: str = Field(
         ..., description="""Description of what this table region points to."""
     )
+    table: DynamicTable = Field(
+        ..., description="""Reference to the DynamicTable object that this region applies to."""
+    )
     value: Optional[
         Union[
             NDArray[Shape["* dim0"], Any],
@@ -1041,9 +1041,6 @@ class DynamicTable(DynamicTableMixin):
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
     )
-    vector_index: Optional[List[VectorIndex]] = Field(
-        None, description="""Indices for the vector columns of this dynamic table."""
-    )
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_2_0/hdmf_common_table.py

@@ -974,12 +974,12 @@ class DynamicTableRegion(DynamicTableRegionMixin, VectorData):
     )
 
     name: str = Field(...)
-    table: DynamicTable = Field(
-        ..., description="""Reference to the DynamicTable object that this region applies to."""
-    )
     description: str = Field(
         ..., description="""Description of what this table region points to."""
     )
+    table: DynamicTable = Field(
+        ..., description="""Reference to the DynamicTable object that this region applies to."""
+    )
     value: Optional[
         Union[
             NDArray[Shape["* dim0"], Any],

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_2_1/hdmf_common_base.py

@@ -171,10 +171,10 @@ class SimpleMultiContainer(Container):
         {"from_schema": "hdmf-common.base", "tree_root": True}
     )
 
-    value: Optional[List[Container]] = Field(
+    name: str = Field(...)
+    value: Optional[Dict[str, Container]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "Container"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_2_1/hdmf_common_table.py

@@ -974,12 +974,12 @@ class DynamicTableRegion(DynamicTableRegionMixin, VectorData):
     )
 
     name: str = Field(...)
-    table: DynamicTable = Field(
-        ..., description="""Reference to the DynamicTable object that this region applies to."""
-    )
     description: str = Field(
         ..., description="""Description of what this table region points to."""
     )
+    table: DynamicTable = Field(
+        ..., description="""Reference to the DynamicTable object that this region applies to."""
+    )
     value: Optional[
         Union[
             NDArray[Shape["* dim0"], Any],

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_3_0/hdmf_common_base.py

@@ -171,10 +171,10 @@ class SimpleMultiContainer(Container):
         {"from_schema": "hdmf-common.base", "tree_root": True}
     )
 
-    value: Optional[List[Container]] = Field(
+    name: str = Field(...)
+    value: Optional[Dict[str, Container]] = Field(
         None, json_schema_extra={"linkml_meta": {"any_of": [{"range": "Container"}]}}
     )
-    name: str = Field(...)
 
 
 # Model rebuild

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_3_0/hdmf_common_sparse.py

@@ -169,23 +169,15 @@ class CSRMatrix(Container):
             "linkml_meta": {"array": {"dimensions": [{"alias": "number_of_rows_in_the_matrix_1"}]}}
         },
     )
-    data: CSRMatrixData = Field(..., description="""The non-zero values in the matrix.""")
+    data: NDArray[Shape["* number_of_non_zero_values"], Any] = Field(
-
+        ...,
-
+        description="""The non-zero values in the matrix.""",
-class CSRMatrixData(ConfiguredBaseModel):
+        json_schema_extra={
-    """
+            "linkml_meta": {"array": {"dimensions": [{"alias": "number_of_non_zero_values"}]}}
-    The non-zero values in the matrix.
+        },
-    """
-
-    linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "hdmf-common.sparse"})
-
-    name: Literal["data"] = Field(
-        "data",
-        json_schema_extra={"linkml_meta": {"equals_string": "data", "ifabsent": "string(data)"}},
     )
 
 
 # Model rebuild
 # see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
 CSRMatrix.model_rebuild()
-CSRMatrixData.model_rebuild()

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_3_0/hdmf_common_table.py

@@ -974,12 +974,12 @@ class DynamicTableRegion(DynamicTableRegionMixin, VectorData):
     )
 
     name: str = Field(...)
-    table: DynamicTable = Field(
-        ..., description="""Reference to the DynamicTable object that this region applies to."""
-    )
     description: str = Field(
         ..., description="""Description of what this table region points to."""
     )
+    table: DynamicTable = Field(
+        ..., description="""Reference to the DynamicTable object that this region applies to."""
+    )
     value: Optional[
         Union[
             NDArray[Shape["* dim0"], Any],

nwb_models/src/nwb_models/models/pydantic/hdmf_common/v1_3_0/namespace.py

@@ -18,7 +18,7 @@ from ...hdmf_common.v1_3_0.hdmf_common_resources import (
     ExternalResourcesObjects,
     ExternalResourcesResources,
 )
-from ...hdmf_common.v1_3_0.hdmf_common_sparse import CSRMatrix, CSRMatrixData
+from ...hdmf_common.v1_3_0.hdmf_common_sparse import CSRMatrix
 from ...hdmf_common.v1_3_0.hdmf_common_table import (
     DynamicTable,
     DynamicTableRegion,

nwb_models/src/nwb_models/models/pydantic/hdmf_experimental/v0_1_0/hdmf_experimental_experimental.py

@@ -11,7 +11,7 @@ import numpy as np
 from numpydantic import NDArray, Shape
 from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator, model_validator
 
-from ...hdmf_common.v1_4_0.hdmf_common_table import VectorData
+from ...hdmf_common.v1_5_0.hdmf_common_table import VectorData
 
 
 metamodel_version = "None"
@@ -136,7 +136,7 @@ linkml_meta = LinkMLMeta(
         },
         "default_prefix": "hdmf-experimental.experimental/",
         "id": "hdmf-experimental.experimental",
-        "imports": ["../../hdmf_common/v1_4_0/namespace", "hdmf-experimental.nwb.language"],
+        "imports": ["../../hdmf_common/v1_5_0/namespace", "hdmf-experimental.nwb.language"],
         "name": "hdmf-experimental.experimental",
     }
 )

nwb_models/src/nwb_models/models/pydantic/hdmf_experimental/v0_1_0/hdmf_experimental_resources.py

@@ -11,7 +11,7 @@ import numpy as np
 from numpydantic import NDArray, Shape
 from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator, model_validator
 
-from ...hdmf_common.v1_4_0.hdmf_common_base import Container, Data
+from ...hdmf_common.v1_5_0.hdmf_common_base import Container, Data
 
 
 metamodel_version = "None"
@@ -136,7 +136,7 @@ linkml_meta = LinkMLMeta(
         },
         "default_prefix": "hdmf-experimental.resources/",
         "id": "hdmf-experimental.resources",
-        "imports": ["../../hdmf_common/v1_4_0/namespace", "hdmf-experimental.nwb.language"],
+        "imports": ["../../hdmf_common/v1_5_0/namespace", "hdmf-experimental.nwb.language"],
         "name": "hdmf-experimental.resources",
     }
 )

nwb_models/src/nwb_models/models/pydantic/hdmf_experimental/v0_1_0/namespace.py

@@ -10,9 +10,10 @@ from typing import Any, ClassVar, Dict, List, Literal, Optional, Union
 import numpy as np
 from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator, model_validator
 
-from ...hdmf_common.v1_4_0.hdmf_common_base import Container, Data, SimpleMultiContainer
+from ...hdmf_common.v1_5_0.hdmf_common_base import Container, Data, SimpleMultiContainer
-from ...hdmf_common.v1_4_0.hdmf_common_sparse import CSRMatrix
+from ...hdmf_common.v1_5_0.hdmf_common_sparse import CSRMatrix
-from ...hdmf_common.v1_4_0.hdmf_common_table import (
+from ...hdmf_common.v1_5_0.hdmf_common_table import (
+    AlignedDynamicTable,
     DynamicTable,
     DynamicTableRegion,
     ElementIdentifiers,

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.base.yaml

@@ -20,6 +20,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -32,6 +33,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       resolution:
@@ -73,6 +75,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -84,6 +87,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -94,6 +98,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -118,15 +123,14 @@ classes:
           external file.
         range: TimeSeries__data
         required: true
-        multivalued: false
+        inlined: true
       starting_time:
         name: starting_time
         description: Timestamp of the first sample in seconds. When timestamps are
           uniformly spaced, the timestamp of the first sample can be specified and
           all subsequent ones calculated from the sampling rate attribute.
         range: TimeSeries__starting_time
-        required: false
+        inlined: true
-        multivalued: false
       timestamps:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
@@ -168,8 +172,8 @@ classes:
           external to the NWB file, in files storing raw data. Once timestamp data
           is calculated, the contents of 'sync' are mostly for archival purposes.
         range: TimeSeries__sync
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
     tree_root: true
   TimeSeries__data:
     name: TimeSeries__data
@@ -180,6 +184,7 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
@@ -244,6 +249,7 @@ classes:
       name:
         name: name
         ifabsent: string(starting_time)
+        identifier: true
         range: string
         required: true
         equals_string: starting_time
@@ -275,6 +281,7 @@ classes:
       name:
         name: name
         ifabsent: string(sync)
+        identifier: true
         range: string
         required: true
         equals_string: sync
@@ -283,13 +290,24 @@ classes:
     description: A collection of processed data.
     is_a: NWBContainer
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        identifier: true
-      inlined_as_list: false
+        range: string
-      any_of:
+        required: true
-      - range: NWBDataInterface
+      description:
-      - range: DynamicTable
+        name: description
+        description: Description of this collection of processed data.
+        range: text
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: NWBDataInterface
+        - range: DynamicTable
     tree_root: true
   Images:
     name: Images
@@ -299,6 +317,7 @@ classes:
       name:
         name: name
         ifabsent: string(Images)
+        identifier: true
         range: string
         required: true
       description:

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.behavior.yaml

@@ -29,6 +29,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -37,13 +38,11 @@ classes:
           reference frame.
         range: SpatialSeries__data
         required: true
-        multivalued: false
+        inlined: true
       reference_frame:
         name: reference_frame
         description: Description defining what exactly 'straight-ahead' means.
         range: text
-        required: false
-        multivalued: false
     tree_root: true
   SpatialSeries__data:
     name: SpatialSeries__data
@@ -53,9 +52,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. The default
@@ -91,12 +114,19 @@ classes:
       events. BehavioralTimeSeries is for continuous data.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralEpochs)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: IntervalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: IntervalSeries
     tree_root: true
   BehavioralEvents:
     name: BehavioralEvents
@@ -104,12 +134,19 @@ classes:
       for more details.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralEvents)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   BehavioralTimeSeries:
     name: BehavioralTimeSeries
@@ -117,36 +154,57 @@ classes:
       of <a href="#BehavioralEpochs">BehavioralEpochs</a> for more details.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralTimeSeries)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   PupilTracking:
     name: PupilTracking
     description: Eye-tracking data, representing pupil size.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(PupilTracking)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   EyeTracking:
     name: EyeTracking
     description: Eye-tracking data, representing direction of gaze.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(EyeTracking)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true
   CompassDirection:
     name: CompassDirection
@@ -157,22 +215,36 @@ classes:
       be radians or degrees.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(CompassDirection)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true
   Position:
     name: Position
     description: Position data, whether along the x, x/y or x/y/z axis.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(Position)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.device.yaml

@@ -21,6 +21,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.ecephys.yaml

@@ -25,41 +25,9 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
-      data:
-        name: data
-        description: Recorded voltage data.
-        range: numeric
-        required: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_times
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_channels
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_channels
-            - alias: num_samples
-      electrodes:
-        name: electrodes
-        annotations:
-          named:
-            tag: named
-            value: true
-          source_type:
-            tag: source_type
-            value: neurodata_type_inc
-        description: DynamicTableRegion pointer to the electrodes that this time series
-          was generated from.
-        range: DynamicTableRegion
-        required: true
-        multivalued: false
       channel_conversion:
         name: channel_conversion
         description: Channel-specific conversion factor. Multiply the data in the
@@ -77,7 +45,87 @@ classes:
         range: float32
         required: false
         multivalued: false
+      data:
+        name: data
+        description: Recorded voltage data.
+        range: ElectricalSeries__data
+        required: true
+        inlined: true
+      electrodes:
+        name: electrodes
+        annotations:
+          named:
+            tag: named
+            value: true
+          source_type:
+            tag: source_type
+            value: neurodata_type_inc
+        description: DynamicTableRegion pointer to the electrodes that this time series
+          was generated from.
+        range: DynamicTableRegion
+        required: true
+        inlined: true
     tree_root: true
+  ElectricalSeries__data:
+    name: ElectricalSeries__data
+    description: Recorded voltage data.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. This value
+          is fixed to 'volts'. Actual stored values are not necessarily stored in
+          these units. To access the data in these units, multiply 'data' by 'conversion'
+          and 'channel_conversion' (if present).
+        ifabsent: string(volts)
+        range: text
+        required: true
+        equals_string: volts
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_times
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_channels
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_channels
+            - alias: num_samples
   SpikeEventSeries:
     name: SpikeEventSeries
     description: 'Stores snapshots/snippets of recorded spike events (i.e., threshold
@@ -92,24 +140,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Spike waveforms.
-        range: numeric
+        range: SpikeEventSeries__data
         required: true
-        multivalued: false
+        inlined: true
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_events
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_events
-            - alias: num_channels
-            - alias: num_samples
       timestamps:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
@@ -123,6 +162,60 @@ classes:
         required: true
         multivalued: false
     tree_root: true
+  SpikeEventSeries__data:
+    name: SpikeEventSeries__data
+    description: Spike waveforms.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement for waveforms, which is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: true
+        equals_string: volts
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_events
+            - alias: num_samples
+        - array:
+            dimensions:
+            - alias: num_events
+            - alias: num_channels
+            - alias: num_samples
   FeatureExtraction:
     name: FeatureExtraction
     description: Features, such as PC1 and PC2, that are extracted from signals stored
@@ -132,6 +225,7 @@ classes:
       name:
         name: name
         ifabsent: string(FeatureExtraction)
+        identifier: true
         range: string
         required: true
       description:
@@ -177,7 +271,7 @@ classes:
           was generated from.
         range: DynamicTableRegion
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   EventDetection:
     name: EventDetection
@@ -187,6 +281,7 @@ classes:
       name:
         name: name
         ifabsent: string(EventDetection)
+        identifier: true
         range: string
         required: true
       detection_method:
@@ -195,7 +290,6 @@ classes:
           or dV/dT threshold, as well as relevant values.
         range: text
         required: true
-        multivalued: false
       source_idx:
         name: source_idx
         description: Indices (zero-based) into source ElectricalSeries::data array
@@ -224,7 +318,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ElectricalSeries
         - range: string
@@ -236,12 +330,19 @@ classes:
       during experiment acquisition.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(EventWaveform)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpikeEventSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpikeEventSeries
     tree_root: true
   FilteredEphys:
     name: FilteredEphys
@@ -258,12 +359,19 @@ classes:
       the ElectricalSeries.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(FilteredEphys)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: ElectricalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: ElectricalSeries
     tree_root: true
   LFP:
     name: LFP
@@ -272,12 +380,19 @@ classes:
       properties should be noted in the ElectricalSeries description or comments field.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(LFP)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: ElectricalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: ElectricalSeries
     tree_root: true
   ElectrodeGroup:
     name: ElectrodeGroup
@@ -286,6 +401,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -304,8 +420,7 @@ classes:
         name: position
         description: stereotaxic or common framework coordinates
         range: ElectrodeGroup__position
-        required: false
+        inlined: true
-        multivalued: false
       device:
         name: device
         annotations:
@@ -313,7 +428,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -325,6 +440,7 @@ classes:
       name:
         name: name
         ifabsent: string(position)
+        identifier: true
         range: string
         required: true
         equals_string: position
@@ -334,24 +450,18 @@ classes:
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
       y:
         name: y
         description: y coordinate
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
       z:
         name: z
         description: z coordinate
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
   ClusterWaveforms:
     name: ClusterWaveforms
     description: DEPRECATED The mean waveform shape, including standard deviation,
@@ -365,6 +475,7 @@ classes:
       name:
         name: name
         ifabsent: string(ClusterWaveforms)
+        identifier: true
         range: string
         required: true
       waveform_filtering:
@@ -372,7 +483,6 @@ classes:
         description: Filtering applied to data before generating mean/sd
         range: text
         required: true
-        multivalued: false
       waveform_mean:
         name: waveform_mean
         description: The mean waveform for each cluster, using the same indices for
@@ -404,7 +514,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Clustering
         - range: string
@@ -418,6 +528,7 @@ classes:
       name:
         name: name
         ifabsent: string(Clustering)
+        identifier: true
         range: string
         required: true
       description:
@@ -426,7 +537,6 @@ classes:
           clusters curated using Klusters, etc)
         range: text
         required: true
-        multivalued: false
       num:
         name: num
         description: Cluster number of each event

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.epoch.yaml

@@ -22,6 +22,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       start_time:
@@ -62,14 +63,12 @@ classes:
             value: neurodata_type_inc
         description: Index for tags.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
       timeseries:
         name: timeseries
         description: An index into a TimeSeries object.
         range: TimeIntervals__timeseries
-        required: false
+        inlined: true
-        multivalued: false
       timeseries_index:
         name: timeseries_index
         annotations:
@@ -81,8 +80,7 @@ classes:
             value: neurodata_type_inc
         description: Index for timeseries.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
     tree_root: true
   TimeIntervals__timeseries:
     name: TimeIntervals__timeseries
@@ -92,6 +90,7 @@ classes:
       name:
         name: name
         ifabsent: string(timeseries)
+        identifier: true
         range: string
         required: true
         equals_string: timeseries
@@ -103,8 +102,6 @@ classes:
         array:
           exact_number_dimensions: 1
         range: int32
-        required: false
-        multivalued: false
       count:
         name: count
         description: Number of data samples available in this time series, during
@@ -112,13 +109,10 @@ classes:
         array:
           exact_number_dimensions: 1
         range: int32
-        required: false
-        multivalued: false
       timeseries:
         name: timeseries
         description: the TimeSeries that this index applies to.
         array:
           exact_number_dimensions: 1
         range: TimeSeries
-        required: false
+        inlined: true
-        multivalued: false

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.file.yaml

@@ -30,6 +30,7 @@ classes:
       name:
         name: name
         ifabsent: string(root)
+        identifier: true
         range: string
         required: true
         equals_string: root
@@ -64,13 +65,11 @@ classes:
           other files.
         range: text
         required: true
-        multivalued: false
       session_description:
         name: session_description
         description: A description of the experimental session and data in the file.
         range: text
         required: true
-        multivalued: false
       session_start_time:
         name: session_start_time
         description: 'Date and time of the experiment/session start. The date is stored
@@ -79,7 +78,6 @@ classes:
           offset. Date accuracy is up to milliseconds.'
         range: isodatetime
         required: true
-        multivalued: false
       timestamps_reference_time:
         name: timestamps_reference_time
         description: 'Date and time corresponding to time zero of all timestamps.
@@ -89,7 +87,6 @@ classes:
           times stored in the file use this time as reference (i.e., time zero).'
         range: isodatetime
         required: true
-        multivalued: false
       acquisition:
         name: acquisition
         description: Data streams recorded from the system, including ephys, ophys,
@@ -168,7 +165,8 @@ classes:
           can exist in the present file or can be linked to a remote library file.
         range: NWBFile__stimulus
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       general:
         name: general
         description: Experimental metadata, including protocol, notes and description
@@ -188,7 +186,8 @@ classes:
           should not be created unless there is data to store within them.
         range: NWBFile__general
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       intervals:
         name: intervals
         description: Experimental intervals, whether that be logically distinct sub-experiments
@@ -196,14 +195,18 @@ classes:
           an experiment, or epochs (see epochs subgroup) deriving from analysis of
           data.
         range: NWBFile__intervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       units:
         name: units
         description: Data about sorted spike units.
         range: Units
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
+      specifications:
+        name: specifications
+        description: Nested dictionary of schema specifications
+        range: dict
     tree_root: true
   NWBFile__stimulus:
     name: NWBFile__stimulus
@@ -223,6 +226,7 @@ classes:
       name:
         name: name
         ifabsent: string(stimulus)
+        identifier: true
         range: string
         required: true
         equals_string: stimulus
@@ -265,6 +269,7 @@ classes:
       name:
         name: name
         ifabsent: string(general)
+        identifier: true
         range: string
         required: true
         equals_string: general
@@ -272,14 +277,10 @@ classes:
         name: data_collection
         description: Notes about data collection and analysis.
         range: text
-        required: false
-        multivalued: false
       experiment_description:
         name: experiment_description
         description: General description of the experiment.
         range: text
-        required: false
-        multivalued: false
       experimenter:
         name: experimenter
         description: Name of person(s) who performed the experiment. Can also specify
@@ -294,8 +295,6 @@ classes:
         name: institution
         description: Institution(s) where experiment was performed.
         range: text
-        required: false
-        multivalued: false
       keywords:
         name: keywords
         description: Terms to search over.
@@ -309,28 +308,20 @@ classes:
         name: lab
         description: Laboratory where experiment was performed.
         range: text
-        required: false
-        multivalued: false
       notes:
         name: notes
         description: Notes about the experiment.
         range: text
-        required: false
-        multivalued: false
       pharmacology:
         name: pharmacology
         description: Description of drugs used, including how and when they were administered.
           Anesthesia(s), painkiller(s), etc., plus dosage, concentration, etc.
         range: text
-        required: false
-        multivalued: false
       protocol:
         name: protocol
         description: Experimental protocol, if applicable. e.g., include IACUC protocol
           number.
         range: text
-        required: false
-        multivalued: false
       related_publications:
         name: related_publications
         description: Publication information. PMID, DOI, URL, etc.
@@ -344,49 +335,39 @@ classes:
         name: session_id
         description: Lab-specific ID for the session.
         range: text
-        required: false
-        multivalued: false
       slices:
         name: slices
         description: Description of slices, including information about preparation
           thickness, orientation, temperature, and bath solution.
         range: text
-        required: false
-        multivalued: false
       source_script:
         name: source_script
         description: Script file or link to public source code used to create this
           NWB file.
         range: general__source_script
-        required: false
+        inlined: true
-        multivalued: false
       stimulus:
         name: stimulus
         description: Notes about stimuli, such as how and where they were presented.
         range: text
-        required: false
-        multivalued: false
       surgery:
         name: surgery
         description: Narrative description about surgery/surgeries, including date(s)
           and who performed surgery.
         range: text
-        required: false
-        multivalued: false
       virus:
         name: virus
         description: Information about virus(es) used in experiments, including virus
           ID, source, date made, injection location, volume, etc.
         range: text
-        required: false
-        multivalued: false
       nwb_container:
         name: nwb_container
         description: Place-holder than can be extended so that lab-specific meta-data
           can be placed in /general.
         range: NWBContainer
-        required: false
         multivalued: true
+        inlined: true
+        inlined_as_list: false
       devices:
         name: devices
         description: Description of hardware devices used during experiment, e.g.,
@@ -401,20 +382,20 @@ classes:
         description: Information about the animal or person from which the data was
           measured.
         range: Subject
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       extracellular_ephys:
         name: extracellular_ephys
         description: Metadata related to extracellular electrophysiology.
         range: general__extracellular_ephys
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       intracellular_ephys:
         name: intracellular_ephys
         description: Metadata related to intracellular electrophysiology.
         range: general__intracellular_ephys
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       optogenetics:
         name: optogenetics
         description: Metadata describing optogenetic stimuluation.
@@ -439,6 +420,7 @@ classes:
       name:
         name: name
         ifabsent: string(source_script)
+        identifier: true
         range: string
         required: true
         equals_string: source_script
@@ -459,6 +441,7 @@ classes:
       name:
         name: name
         ifabsent: string(subject)
+        identifier: true
         range: string
         required: true
         equals_string: subject
@@ -466,52 +449,36 @@ classes:
         name: age
         description: Age of subject. Can be supplied instead of 'date_of_birth'.
         range: text
-        required: false
-        multivalued: false
       date_of_birth:
         name: date_of_birth
         description: Date of birth of subject. Can be supplied instead of 'age'.
         range: isodatetime
-        required: false
-        multivalued: false
       description:
         name: description
         description: Description of subject and where subject came from (e.g., breeder,
           if animal).
         range: text
-        required: false
-        multivalued: false
       genotype:
         name: genotype
         description: Genetic strain. If absent, assume Wild Type (WT).
         range: text
-        required: false
-        multivalued: false
       sex:
         name: sex
         description: Gender of subject.
         range: text
-        required: false
-        multivalued: false
       species:
         name: species
         description: Species of subject.
         range: text
-        required: false
-        multivalued: false
       subject_id:
         name: subject_id
         description: ID of animal/person used/participating in experiment (lab convention).
         range: text
-        required: false
-        multivalued: false
       weight:
         name: weight
         description: Weight at time of experiment, at time of surgery and at other
           important times.
         range: text
-        required: false
-        multivalued: false
   general__extracellular_ephys:
     name: general__extracellular_ephys
     description: Metadata related to extracellular electrophysiology.
@@ -519,21 +486,23 @@ classes:
       name:
         name: name
         ifabsent: string(extracellular_ephys)
+        identifier: true
         range: string
         required: true
         equals_string: extracellular_ephys
-      electrode_group:
-        name: electrode_group
-        description: Physical group of electrodes.
-        range: ElectrodeGroup
-        required: false
-        multivalued: true
       electrodes:
         name: electrodes
         description: A table of all electrodes (i.e. channels) used for recording.
         range: extracellular_ephys__electrodes
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
+      value:
+        name: value
+        description: Physical group of electrodes.
+        range: ElectrodeGroup
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
   extracellular_ephys__electrodes:
     name: extracellular_ephys__electrodes
     description: A table of all electrodes (i.e. channels) used for recording.
@@ -542,6 +511,7 @@ classes:
       name:
         name: name
         ifabsent: string(electrodes)
+        identifier: true
         range: string
         required: true
         equals_string: electrodes
@@ -604,9 +574,13 @@ classes:
       group:
         name: group
         description: Reference to the ElectrodeGroup this electrode is a part of.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
         range: ElectrodeGroup
         required: true
-        multivalued: true
+        multivalued: false
+        inlined: true
       group_name:
         name: group_name
         description: Name of the ElectrodeGroup this electrode is a part of.
@@ -659,6 +633,7 @@ classes:
       name:
         name: name
         ifabsent: string(intracellular_ephys)
+        identifier: true
         range: string
         required: true
         equals_string: intracellular_ephys
@@ -668,20 +643,19 @@ classes:
           frequency fall-off, etc. If this changes between TimeSeries, filter description
           should be stored as a text attribute for each TimeSeries.
         range: text
-        required: false
-        multivalued: false
-      intracellular_electrode:
-        name: intracellular_electrode
-        description: An intracellular electrode.
-        range: IntracellularElectrode
-        required: false
-        multivalued: true
       sweep_table:
         name: sweep_table
         description: The table which groups different PatchClampSeries together.
         range: SweepTable
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
+      value:
+        name: value
+        description: An intracellular electrode.
+        range: IntracellularElectrode
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
   NWBFile__intervals:
     name: NWBFile__intervals
     description: Experimental intervals, whether that be logically distinct sub-experiments
@@ -691,6 +665,7 @@ classes:
       name:
         name: name
         ifabsent: string(intervals)
+        identifier: true
         range: string
         required: true
         equals_string: intervals
@@ -699,24 +674,25 @@ classes:
         description: Divisions in time marking experimental stages or sub-divisions
           of a single recording session.
         range: TimeIntervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
       trials:
         name: trials
         description: Repeated experimental events that have a logical grouping.
         range: TimeIntervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
       invalid_times:
         name: invalid_times
         description: Time intervals that should be removed from analysis.
         range: TimeIntervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
-      time_intervals:
+      value:
-        name: time_intervals
+        name: value
         description: Optional additional table(s) for describing other experimental
           time intervals.
         range: TimeIntervals
-        required: false
         multivalued: true
+        inlined: true
+        inlined_as_list: false

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.icephys.yaml

@@ -23,6 +23,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       stimulus_description:
@@ -40,14 +41,12 @@ classes:
         description: Recorded voltage or current.
         range: PatchClampSeries__data
         required: true
-        multivalued: false
+        inlined: true
       gain:
         name: gain
         description: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt
           (c-clamp).
         range: float32
-        required: false
-        multivalued: false
       electrode:
         name: electrode
         annotations:
@@ -55,7 +54,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: IntracellularElectrode
         - range: string
@@ -67,9 +66,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. Actual stored
@@ -92,32 +115,27 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
+      bias_current:
+        name: bias_current
+        description: Bias current, in amps.
+        range: float32
+      bridge_balance:
+        name: bridge_balance
+        description: Bridge balance, in ohms.
+        range: float32
+      capacitance_compensation:
+        name: capacitance_compensation
+        description: Capacitance compensation, in farads.
+        range: float32
       data:
         name: data
         description: Recorded voltage.
         range: CurrentClampSeries__data
         required: true
-        multivalued: false
+        inlined: true
-      bias_current:
-        name: bias_current
-        description: Bias current, in amps.
-        range: float32
-        required: false
-        multivalued: false
-      bridge_balance:
-        name: bridge_balance
-        description: Bridge balance, in ohms.
-        range: float32
-        required: false
-        multivalued: false
-      capacitance_compensation:
-        name: capacitance_compensation
-        description: Capacitance compensation, in farads.
-        range: float32
-        required: false
-        multivalued: false
     tree_root: true
   CurrentClampSeries__data:
     name: CurrentClampSeries__data
@@ -126,9 +144,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -140,8 +182,10 @@ classes:
         equals_string: volts
       value:
         name: value
-        range: AnyType
+        array:
-        required: true
+          dimensions:
+          - alias: num_times
+        range: numeric
   IZeroClampSeries:
     name: IZeroClampSeries
     description: Voltage data from an intracellular recording when all current and
@@ -152,6 +196,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       bias_current:
@@ -159,19 +204,16 @@ classes:
         description: Bias current, in amps, fixed to 0.0.
         range: float32
         required: true
-        multivalued: false
       bridge_balance:
         name: bridge_balance
         description: Bridge balance, in ohms, fixed to 0.0.
         range: float32
         required: true
-        multivalued: false
       capacitance_compensation:
         name: capacitance_compensation
         description: Capacitance compensation, in farads, fixed to 0.0.
         range: float32
         required: true
-        multivalued: false
     tree_root: true
   CurrentClampStimulusSeries:
     name: CurrentClampStimulusSeries
@@ -180,6 +222,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -187,7 +230,7 @@ classes:
         description: Stimulus current applied.
         range: CurrentClampStimulusSeries__data
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   CurrentClampStimulusSeries__data:
     name: CurrentClampStimulusSeries__data
@@ -196,9 +239,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -210,8 +277,10 @@ classes:
         equals_string: amperes
       value:
         name: value
-        range: AnyType
+        array:
-        required: true
+          dimensions:
+          - alias: num_times
+        range: numeric
   VoltageClampSeries:
     name: VoltageClampSeries
     description: Current data from an intracellular voltage-clamp recording. A corresponding
@@ -221,80 +290,51 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
+      capacitance_fast:
+        name: capacitance_fast
+        description: Fast capacitance, in farads.
+        range: VoltageClampSeries__capacitance_fast
+        inlined: true
+      capacitance_slow:
+        name: capacitance_slow
+        description: Slow capacitance, in farads.
+        range: VoltageClampSeries__capacitance_slow
+        inlined: true
       data:
         name: data
         description: Recorded current.
         range: VoltageClampSeries__data
         required: true
-        multivalued: false
+        inlined: true
-      capacitance_fast:
-        name: capacitance_fast
-        description: Fast capacitance, in farads.
-        range: VoltageClampSeries__capacitance_fast
-        required: false
-        multivalued: false
-      capacitance_slow:
-        name: capacitance_slow
-        description: Slow capacitance, in farads.
-        range: VoltageClampSeries__capacitance_slow
-        required: false
-        multivalued: false
       resistance_comp_bandwidth:
         name: resistance_comp_bandwidth
         description: Resistance compensation bandwidth, in hertz.
         range: VoltageClampSeries__resistance_comp_bandwidth
-        required: false
+        inlined: true
-        multivalued: false
       resistance_comp_correction:
         name: resistance_comp_correction
         description: Resistance compensation correction, in percent.
         range: VoltageClampSeries__resistance_comp_correction
-        required: false
+        inlined: true
-        multivalued: false
       resistance_comp_prediction:
         name: resistance_comp_prediction
         description: Resistance compensation prediction, in percent.
         range: VoltageClampSeries__resistance_comp_prediction
-        required: false
+        inlined: true
-        multivalued: false
       whole_cell_capacitance_comp:
         name: whole_cell_capacitance_comp
         description: Whole cell capacitance compensation, in farads.
         range: VoltageClampSeries__whole_cell_capacitance_comp
-        required: false
+        inlined: true
-        multivalued: false
       whole_cell_series_resistance_comp:
         name: whole_cell_series_resistance_comp
         description: Whole cell series resistance compensation, in ohms.
         range: VoltageClampSeries__whole_cell_series_resistance_comp
-        required: false
+        inlined: true
-        multivalued: false
     tree_root: true
-  VoltageClampSeries__data:
-    name: VoltageClampSeries__data
-    description: Recorded current.
-    attributes:
-      name:
-        name: name
-        ifabsent: string(data)
-        range: string
-        required: true
-        equals_string: data
-      unit:
-        name: unit
-        description: Base unit of measurement for working with the data. which is
-          fixed to 'amperes'. Actual stored values are not necessarily stored in these
-          units. To access the data in these units, multiply 'data' by 'conversion'.
-        ifabsent: string(amperes)
-        range: text
-        required: true
-        equals_string: amperes
-      value:
-        name: value
-        range: AnyType
-        required: true
   VoltageClampSeries__capacitance_fast:
     name: VoltageClampSeries__capacitance_fast
     description: Fast capacitance, in farads.
@@ -302,6 +342,7 @@ classes:
       name:
         name: name
         ifabsent: string(capacitance_fast)
+        identifier: true
         range: string
         required: true
         equals_string: capacitance_fast
@@ -323,6 +364,7 @@ classes:
       name:
         name: name
         ifabsent: string(capacitance_slow)
+        identifier: true
         range: string
         required: true
         equals_string: capacitance_slow
@@ -337,6 +379,55 @@ classes:
         name: value
         range: float32
         required: true
+  VoltageClampSeries__data:
+    name: VoltageClampSeries__data
+    description: Recorded current.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. which is
+          fixed to 'amperes'. Actual stored values are not necessarily stored in these
+          units. To access the data in these units, multiply 'data' by 'conversion'.
+        ifabsent: string(amperes)
+        range: text
+        required: true
+        equals_string: amperes
+      value:
+        name: value
+        array:
+          dimensions:
+          - alias: num_times
+        range: numeric
   VoltageClampSeries__resistance_comp_bandwidth:
     name: VoltageClampSeries__resistance_comp_bandwidth
     description: Resistance compensation bandwidth, in hertz.
@@ -344,6 +435,7 @@ classes:
       name:
         name: name
         ifabsent: string(resistance_comp_bandwidth)
+        identifier: true
         range: string
         required: true
         equals_string: resistance_comp_bandwidth
@@ -366,6 +458,7 @@ classes:
       name:
         name: name
         ifabsent: string(resistance_comp_correction)
+        identifier: true
         range: string
         required: true
         equals_string: resistance_comp_correction
@@ -388,6 +481,7 @@ classes:
       name:
         name: name
         ifabsent: string(resistance_comp_prediction)
+        identifier: true
         range: string
         required: true
         equals_string: resistance_comp_prediction
@@ -410,6 +504,7 @@ classes:
       name:
         name: name
         ifabsent: string(whole_cell_capacitance_comp)
+        identifier: true
         range: string
         required: true
         equals_string: whole_cell_capacitance_comp
@@ -432,6 +527,7 @@ classes:
       name:
         name: name
         ifabsent: string(whole_cell_series_resistance_comp)
+        identifier: true
         range: string
         required: true
         equals_string: whole_cell_series_resistance_comp
@@ -454,6 +550,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -461,7 +558,7 @@ classes:
         description: Stimulus voltage applied.
         range: VoltageClampStimulusSeries__data
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   VoltageClampStimulusSeries__data:
     name: VoltageClampStimulusSeries__data
@@ -470,9 +567,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -484,8 +605,10 @@ classes:
         equals_string: volts
       value:
         name: value
-        range: AnyType
+        array:
-        required: true
+          dimensions:
+          - alias: num_times
+        range: numeric
   IntracellularElectrode:
     name: IntracellularElectrode
     description: An intracellular electrode and its metadata.
@@ -493,6 +616,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -500,45 +624,32 @@ classes:
         description: Description of electrode (e.g.,  whole-cell, sharp, etc.).
         range: text
         required: true
-        multivalued: false
       filtering:
         name: filtering
         description: Electrode specific filtering.
         range: text
-        required: false
-        multivalued: false
       initial_access_resistance:
         name: initial_access_resistance
         description: Initial access resistance.
         range: text
-        required: false
-        multivalued: false
       location:
         name: location
         description: Location of the electrode. Specify the area, layer, comments
           on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use
           standard atlas names for anatomical regions when possible.
         range: text
-        required: false
-        multivalued: false
       resistance:
         name: resistance
         description: Electrode resistance, in ohms.
         range: text
-        required: false
-        multivalued: false
       seal:
         name: seal
         description: Information about seal used for recording.
         range: text
-        required: false
-        multivalued: false
       slice:
         name: slice
         description: Information about slice used for recording.
         range: text
-        required: false
-        multivalued: false
       device:
         name: device
         annotations:
@@ -546,7 +657,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -558,23 +669,19 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
-      sweep_number:
-        name: sweep_number
-        description: Sweep number of the PatchClampSeries in that row.
-        array:
-          minimum_number_dimensions: 1
-          maximum_number_dimensions: false
-        range: uint32
-        required: true
-        multivalued: false
       series:
         name: series
         description: The PatchClampSeries with the sweep number in that row.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
         range: PatchClampSeries
         required: true
-        multivalued: true
+        multivalued: false
+        inlined: true
       series_index:
         name: series_index
         annotations:
@@ -587,5 +694,14 @@ classes:
         description: Index for series.
         range: VectorIndex
         required: true
+        inlined: true
+      sweep_number:
+        name: sweep_number
+        description: Sweep number of the PatchClampSeries in that row.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
+        range: uint32
+        required: true
         multivalued: false
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.image.yaml

@@ -20,6 +20,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       value:
@@ -37,6 +38,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       value:
@@ -56,6 +58,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       value:
@@ -80,26 +83,14 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Binary data representing images across frames.
-        range: numeric
+        range: ImageSeries__data
-        required: false
+        inlined: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: frame
-            - alias: x
-            - alias: y
-        - array:
-            dimensions:
-            - alias: frame
-            - alias: x
-            - alias: y
-            - alias: z
       dimension:
         name: dimension
         description: Number of pixels on x, y, (and z) axes.
@@ -117,18 +108,72 @@ classes:
           used if the image is stored in another NWB file and that file is linked
           to this file.
         range: ImageSeries__external_file
-        required: false
+        inlined: true
-        multivalued: false
       format:
         name: format
         description: Format of image. If this is 'external', then the attribute 'external_file'
           contains the path information to the image files. If this is 'raw', then
           the raw (single-channel) binary data is stored in the 'data' dataset. If
           this attribute is not present, then the default format='raw' case is assumed.
+        ifabsent: string(raw)
         range: text
-        required: false
-        multivalued: false
     tree_root: true
+  ImageSeries__data:
+    name: ImageSeries__data
+    description: Binary data representing images across frames.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Actual stored
+          values are not necessarily stored in these units. To access the data in
+          these units, multiply 'data' by 'conversion'.
+        range: text
+        required: true
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: frame
+            - alias: x
+            - alias: y
+        - array:
+            dimensions:
+            - alias: frame
+            - alias: x
+            - alias: y
+            - alias: z
   ImageSeries__external_file:
     name: ImageSeries__external_file
     description: Paths to one or more external file(s). The field is only present
@@ -139,6 +184,7 @@ classes:
       name:
         name: name
         ifabsent: string(external_file)
+        identifier: true
         range: string
         required: true
         equals_string: external_file
@@ -176,6 +222,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       masked_imageseries:
@@ -185,7 +232,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ImageSeries
         - range: string
@@ -201,14 +248,13 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       distance:
         name: distance
         description: Distance from camera/monitor to target/eye.
         range: float32
-        required: false
-        multivalued: false
       field_of_view:
         name: field_of_view
         description: Width, height and depth of image, or imaged area, in meters.
@@ -229,8 +275,6 @@ classes:
         description: Description of image relative to some reference frame (e.g.,
           which way is up). Must also specify frame of reference.
         range: text
-        required: false
-        multivalued: false
     tree_root: true
   IndexSeries:
     name: IndexSeries
@@ -244,17 +288,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Index of the frame in the referenced ImageSeries.
-        array:
+        range: IndexSeries__data
-          dimensions:
-          - alias: num_times
-        range: int32
         required: true
-        multivalued: false
+        inlined: true
       indexed_timeseries:
         name: indexed_timeseries
         annotations:
@@ -262,8 +304,55 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ImageSeries
         - range: string
     tree_root: true
+  IndexSeries__data:
+    name: IndexSeries__data
+    description: Index of the frame in the referenced ImageSeries.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Actual stored
+          values are not necessarily stored in these units. To access the data in
+          these units, multiply 'data' by 'conversion'.
+        range: text
+        required: true
+      value:
+        name: value
+        array:
+          dimensions:
+          - alias: num_times
+        range: int32

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.language.yaml

@@ -66,6 +66,7 @@ types:
   numeric:
     name: numeric
     typeof: float
+    repr: float | int
   text:
     name: text
     typeof: string
@@ -87,6 +88,9 @@ types:
   isodatetime:
     name: isodatetime
     typeof: datetime
+  dict:
+    name: dict
+    repr: dict
 classes:
   AnyType:
     name: AnyType

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.misc.yaml

@@ -30,6 +30,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -37,7 +38,7 @@ classes:
         description: Values of each feature at each time.
         range: AbstractFeatureSeries__data
         required: true
-        multivalued: false
+        inlined: true
       feature_units:
         name: feature_units
         description: Units of each feature.
@@ -64,9 +65,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Since there can be different units for different features, store
@@ -96,18 +121,63 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Annotations made during an experiment.
+        range: AnnotationSeries__data
+        required: true
+        inlined: true
+    tree_root: true
+  AnnotationSeries__data:
+    name: AnnotationSeries__data
+    description: Annotations made during an experiment.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data. Annotations
+          have no units, so the value is fixed to -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: true
+        equals_number: -1
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Annotations
+          have no units, so the value is fixed to 'n/a'.
+        ifabsent: string(n/a)
+        range: text
+        required: true
+        equals_string: n/a
+      value:
+        name: value
         array:
           dimensions:
           - alias: num_times
         range: text
-        required: true
-        multivalued: false
-    tree_root: true
   IntervalSeries:
     name: IntervalSeries
     description: Stores intervals of data. The timestamps field stores the beginning
@@ -121,18 +191,63 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Use values >0 if interval started, <0 if interval ended.
+        range: IntervalSeries__data
+        required: true
+        inlined: true
+    tree_root: true
+  IntervalSeries__data:
+    name: IntervalSeries__data
+    description: Use values >0 if interval started, <0 if interval ended.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data. Annotations
+          have no units, so the value is fixed to -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: true
+        equals_number: -1
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Annotations
+          have no units, so the value is fixed to 'n/a'.
+        ifabsent: string(n/a)
+        range: text
+        required: true
+        equals_string: n/a
+      value:
+        name: value
         array:
           dimensions:
           - alias: num_times
         range: int8
-        required: true
-        multivalued: false
-    tree_root: true
   DecompositionSeries:
     name: DecompositionSeries
     description: Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -140,6 +255,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -147,28 +263,27 @@ classes:
         description: Data decomposed into frequency bands.
         range: DecompositionSeries__data
         required: true
-        multivalued: false
+        inlined: true
       metric:
         name: metric
         description: The metric used, e.g. phase, amplitude, power.
         range: text
         required: true
-        multivalued: false
       bands:
         name: bands
         description: Table for describing the bands that this series was generated
           from. There should be one row in this table for each band.
         range: DecompositionSeries__bands
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       source_timeseries:
         name: source_timeseries
         annotations:
           source_type:
             tag: source_type
             value: link
-        required: false
+        inlined: true
-        multivalued: false
         any_of:
         - range: TimeSeries
         - range: string
@@ -180,9 +295,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. Actual stored
@@ -208,6 +347,7 @@ classes:
       name:
         name: name
         ifabsent: string(bands)
+        identifier: true
         range: string
         required: true
         equals_string: bands
@@ -259,10 +399,21 @@ classes:
       name:
         name: name
         ifabsent: string(Units)
+        identifier: true
         range: string
         required: true
-      spike_times_index:
+      electrode_group:
-        name: spike_times_index
+        name: electrode_group
+        description: Electrode group that each spike unit came from.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
+        range: ElectrodeGroup
+        required: false
+        multivalued: false
+        inlined: true
+      electrodes:
+        name: electrodes
         annotations:
           named:
             tag: named
@@ -270,14 +421,30 @@ classes:
           source_type:
             tag: source_type
             value: neurodata_type_inc
-        description: Index into the spike_times dataset.
+        description: Electrode that each spike unit came from, specified using a DynamicTableRegion.
+        range: DynamicTableRegion
+        inlined: true
+      electrodes_index:
+        name: electrodes_index
+        annotations:
+          named:
+            tag: named
+            value: true
+          source_type:
+            tag: source_type
+            value: neurodata_type_inc
+        description: Index into electrodes.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
+      obs_intervals:
-      spike_times:
+        name: obs_intervals
-        name: spike_times
+        description: Observation intervals for each unit.
-        description: Spike times for each unit.
+        array:
-        range: Units__spike_times
+          dimensions:
+          - alias: num_intervals
+          - alias: start_end
+            exact_cardinality: 2
+        range: float64
         required: false
         multivalued: false
       obs_intervals_index:
@@ -291,21 +458,14 @@ classes:
             value: neurodata_type_inc
         description: Index into the obs_intervals dataset.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
+      spike_times:
-      obs_intervals:
+        name: spike_times
-        name: obs_intervals
+        description: Spike times for each unit.
-        description: Observation intervals for each unit.
+        range: Units__spike_times
-        array:
+        inlined: true
-          dimensions:
+      spike_times_index:
-          - alias: num_intervals
+        name: spike_times_index
-          - alias: start_end
-            exact_cardinality: 2
-        range: float64
-        required: false
-        multivalued: false
-      electrodes_index:
-        name: electrodes_index
         annotations:
           named:
             tag: named
@@ -313,61 +473,19 @@ classes:
           source_type:
             tag: source_type
             value: neurodata_type_inc
-        description: Index into electrodes.
+        description: Index into the spike_times dataset.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
-      electrodes:
-        name: electrodes
-        annotations:
-          named:
-            tag: named
-            value: true
-          source_type:
-            tag: source_type
-            value: neurodata_type_inc
-        description: Electrode that each spike unit came from, specified using a DynamicTableRegion.
-        range: DynamicTableRegion
-        required: false
-        multivalued: false
-      electrode_group:
-        name: electrode_group
-        description: Electrode group that each spike unit came from.
-        range: ElectrodeGroup
-        required: false
-        multivalued: true
       waveform_mean:
         name: waveform_mean
         description: Spike waveform mean for each spike unit.
-        range: float32
+        range: Units__waveform_mean
-        required: false
+        inlined: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-            - alias: num_electrodes
       waveform_sd:
         name: waveform_sd
         description: Spike waveform standard deviation for each spike unit.
-        range: float32
+        range: Units__waveform_sd
-        required: false
+        inlined: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-            - alias: num_electrodes
     tree_root: true
   Units__spike_times:
     name: Units__spike_times
@@ -377,6 +495,7 @@ classes:
       name:
         name: name
         ifabsent: string(spike_times)
+        identifier: true
         range: string
         required: true
         equals_string: spike_times
@@ -389,3 +508,51 @@ classes:
           for the spike time to be between samples.
         range: float64
         required: false
+  Units__waveform_mean:
+    name: Units__waveform_mean
+    description: Spike waveform mean for each spike unit.
+    is_a: VectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_mean)
+        identifier: true
+        range: string
+        required: true
+        equals_string: waveform_mean
+      sampling_rate:
+        name: sampling_rate
+        description: Sampling rate, in hertz.
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement. This value is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: false
+        equals_string: volts
+  Units__waveform_sd:
+    name: Units__waveform_sd
+    description: Spike waveform standard deviation for each spike unit.
+    is_a: VectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_sd)
+        identifier: true
+        range: string
+        required: true
+        equals_string: waveform_sd
+      sampling_rate:
+        name: sampling_rate
+        description: Sampling rate, in hertz.
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement. This value is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: false
+        equals_string: volts

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.ogen.yaml

@@ -21,17 +21,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Applied power for optogenetic stimulus, in watts.
-        array:
+        range: OptogeneticSeries__data
-          dimensions:
-          - alias: num_times
-        range: numeric
         required: true
-        multivalued: false
+        inlined: true
       site:
         name: site
         annotations:
@@ -39,11 +37,58 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: OptogeneticStimulusSite
         - range: string
     tree_root: true
+  OptogeneticSeries__data:
+    name: OptogeneticSeries__data
+    description: Applied power for optogenetic stimulus, in watts.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement for data, which is fixed to 'watts'.
+        ifabsent: string(watts)
+        range: text
+        required: true
+        equals_string: watts
+      value:
+        name: value
+        array:
+          dimensions:
+          - alias: num_times
+        range: numeric
   OptogeneticStimulusSite:
     name: OptogeneticStimulusSite
     description: A site of optogenetic stimulation.
@@ -51,6 +96,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -58,13 +104,11 @@ classes:
         description: Description of stimulation site.
         range: text
         required: true
-        multivalued: false
       excitation_lambda:
         name: excitation_lambda
         description: Excitation wavelength, in nm.
         range: float32
         required: true
-        multivalued: false
       location:
         name: location
         description: Location of the stimulation site. Specify the area, layer, comments
@@ -72,7 +116,6 @@ classes:
           standard atlas names for anatomical regions when possible.
         range: text
         required: true
-        multivalued: false
       device:
         name: device
         annotations:
@@ -80,7 +123,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.ophys.yaml

@@ -23,6 +23,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       pmt_gain:
@@ -59,7 +60,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ImagingPlane
         - range: string
@@ -72,22 +73,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Signals from ROIs.
-        range: numeric
+        range: RoiResponseSeries__data
         required: true
-        multivalued: false
+        inlined: true
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_times
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_rois
       rois:
         name: rois
         annotations:
@@ -101,8 +95,60 @@ classes:
           on the ROIs stored in this timeseries.
         range: DynamicTableRegion
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
+  RoiResponseSeries__data:
+    name: RoiResponseSeries__data
+    description: Signals from ROIs.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Actual stored
+          values are not necessarily stored in these units. To access the data in
+          these units, multiply 'data' by 'conversion'.
+        range: text
+        required: true
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_times
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_rois
   DfOverF:
     name: DfOverF
     description: dF/F information about a region of interest (ROI). Storage hierarchy
@@ -110,12 +156,19 @@ classes:
       for image planes).
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(DfOverF)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: RoiResponseSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: RoiResponseSeries
     tree_root: true
   Fluorescence:
     name: Fluorescence
@@ -124,12 +177,19 @@ classes:
       for ROIs and for image planes).
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(Fluorescence)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: RoiResponseSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: RoiResponseSeries
     tree_root: true
   ImageSegmentation:
     name: ImageSegmentation
@@ -142,12 +202,19 @@ classes:
       is required and ROI names should remain consistent between them.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(ImageSegmentation)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: DynamicTable
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: DynamicTable
     tree_root: true
   ImagingPlane:
     name: ImagingPlane
@@ -156,32 +223,28 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
         name: description
         description: Description of the imaging plane.
         range: text
-        required: false
-        multivalued: false
       excitation_lambda:
         name: excitation_lambda
         description: Excitation wavelength, in nm.
         range: float32
         required: true
-        multivalued: false
       imaging_rate:
         name: imaging_rate
         description: Rate that images are acquired, in Hz.
         range: float32
         required: true
-        multivalued: false
       indicator:
         name: indicator
         description: Calcium indicator.
         range: text
         required: true
-        multivalued: false
       location:
         name: location
         description: Location of the imaging plane. Specify the area, layer, comments
@@ -189,31 +252,27 @@ classes:
           standard atlas names for anatomical regions when possible.
         range: text
         required: true
-        multivalued: false
       manifold:
         name: manifold
         description: DEPRECATED Physical position of each pixel. 'xyz' represents
           the position of the pixel relative to the defined coordinate space. Deprecated
           in favor of origin_coords and grid_spacing.
         range: ImagingPlane__manifold
-        required: false
+        inlined: true
-        multivalued: false
       origin_coords:
         name: origin_coords
         description: Physical location of the first element of the imaging plane (0,
           0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for
           what the physical location is relative to (e.g., bregma).
         range: ImagingPlane__origin_coords
-        required: false
+        inlined: true
-        multivalued: false
       grid_spacing:
         name: grid_spacing
         description: Space between pixels in (x, y) or voxels in (x, y, z) directions,
           in the specified unit. Assumes imaging plane is a regular grid. See also
           reference_frame to interpret the grid.
         range: ImagingPlane__grid_spacing
-        required: false
+        inlined: true
-        multivalued: false
       reference_frame:
         name: reference_frame
         description: Describes reference frame of origin_coords and grid_spacing.
@@ -234,14 +293,13 @@ classes:
           axis (larger index = more rightward). Third dimension corresponds to dorsal-ventral
           axis (larger index = more ventral)."
         range: text
-        required: false
-        multivalued: false
       optical_channel:
         name: optical_channel
         description: An optical channel used to record from an imaging plane.
         range: OpticalChannel
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       device:
         name: device
         annotations:
@@ -249,7 +307,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -263,6 +321,7 @@ classes:
       name:
         name: name
         ifabsent: string(manifold)
+        identifier: true
         range: string
         required: true
         equals_string: manifold
@@ -312,6 +371,7 @@ classes:
       name:
         name: name
         ifabsent: string(origin_coords)
+        identifier: true
         range: string
         required: true
         equals_string: origin_coords
@@ -339,6 +399,7 @@ classes:
       name:
         name: name
         ifabsent: string(grid_spacing)
+        identifier: true
         range: string
         required: true
         equals_string: grid_spacing
@@ -364,6 +425,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -371,13 +433,11 @@ classes:
         description: Description or other notes about the channel.
         range: text
         required: true
-        multivalued: false
       emission_lambda:
         name: emission_lambda
         description: Emission wavelength for channel, in nm.
         range: float32
         required: true
-        multivalued: false
   MotionCorrection:
     name: MotionCorrection
     description: 'An image stack where all frames are shifted (registered) to a common
@@ -385,10 +445,17 @@ classes:
       frame at each point in time is assumed to be 2-D (has only x & y dimensions).'
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(MotionCorrection)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: NWBDataInterface
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: NWBDataInterface
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_0/core.nwb.retinotopy.yaml

@@ -21,6 +21,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       dimension:
@@ -52,6 +53,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       unit:
@@ -75,6 +77,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       bits_per_pixel:
@@ -115,6 +118,7 @@ classes:
       name:
         name: name
         ifabsent: string(ImagingRetinotopy)
+        identifier: true
         range: string
         required: true
       axis_1_phase_map:
@@ -129,7 +133,7 @@ classes:
         description: Phase response to stimulus on the first measured axis.
         range: AxisMap
         required: true
-        multivalued: false
+        inlined: true
       axis_1_power_map:
         name: axis_1_power_map
         annotations:
@@ -142,8 +146,7 @@ classes:
         description: Power response on the first measured axis. Response is scaled
           so 0.0 is no power in the response and 1.0 is maximum relative power.
         range: AxisMap
-        required: false
+        inlined: true
-        multivalued: false
       axis_2_phase_map:
         name: axis_2_phase_map
         annotations:
@@ -156,7 +159,7 @@ classes:
         description: Phase response to stimulus on the second measured axis.
         range: AxisMap
         required: true
-        multivalued: false
+        inlined: true
       axis_2_power_map:
         name: axis_2_power_map
         annotations:
@@ -168,8 +171,7 @@ classes:
             value: neurodata_type_inc
         description: Power response to stimulus on the second measured axis.
         range: AxisMap
-        required: false
+        inlined: true
-        multivalued: false
       sign_map:
         name: sign_map
         annotations:
@@ -183,7 +185,7 @@ classes:
           and axis_2.
         range: RetinotopyMap
         required: true
-        multivalued: false
+        inlined: true
       axis_descriptions:
         name: axis_descriptions
         description: Two-element array describing the contents of the two response
@@ -202,7 +204,7 @@ classes:
           focal depth, wavelength) as data collection. Array format: [rows][columns].'
         range: ImagingRetinotopy__focal_depth_image
         required: true
-        multivalued: false
+        inlined: true
       vasculature_image:
         name: vasculature_image
         annotations:
@@ -216,7 +218,7 @@ classes:
           [rows][columns]'
         range: RetinotopyImage
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   ImagingRetinotopy__focal_depth_image:
     name: ImagingRetinotopy__focal_depth_image
@@ -227,6 +229,7 @@ classes:
       name:
         name: name
         ifabsent: string(focal_depth_image)
+        identifier: true
         range: string
         required: true
         equals_string: focal_depth_image

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.base.yaml

@@ -20,6 +20,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -32,6 +33,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       resolution:
@@ -73,6 +75,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -84,6 +87,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -94,6 +98,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -118,15 +123,14 @@ classes:
           external file.
         range: TimeSeries__data
         required: true
-        multivalued: false
+        inlined: true
       starting_time:
         name: starting_time
         description: Timestamp of the first sample in seconds. When timestamps are
           uniformly spaced, the timestamp of the first sample can be specified and
           all subsequent ones calculated from the sampling rate attribute.
         range: TimeSeries__starting_time
-        required: false
+        inlined: true
-        multivalued: false
       timestamps:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
@@ -168,8 +172,8 @@ classes:
           external to the NWB file, in files storing raw data. Once timestamp data
           is calculated, the contents of 'sync' are mostly for archival purposes.
         range: TimeSeries__sync
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
     tree_root: true
   TimeSeries__data:
     name: TimeSeries__data
@@ -180,6 +184,7 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
@@ -244,6 +249,7 @@ classes:
       name:
         name: name
         ifabsent: string(starting_time)
+        identifier: true
         range: string
         required: true
         equals_string: starting_time
@@ -275,6 +281,7 @@ classes:
       name:
         name: name
         ifabsent: string(sync)
+        identifier: true
         range: string
         required: true
         equals_string: sync
@@ -283,13 +290,24 @@ classes:
     description: A collection of processed data.
     is_a: NWBContainer
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        identifier: true
-      inlined_as_list: false
+        range: string
-      any_of:
+        required: true
-      - range: NWBDataInterface
+      description:
-      - range: DynamicTable
+        name: description
+        description: Description of this collection of processed data.
+        range: text
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: NWBDataInterface
+        - range: DynamicTable
     tree_root: true
   Images:
     name: Images
@@ -299,6 +317,7 @@ classes:
       name:
         name: name
         ifabsent: string(Images)
+        identifier: true
         range: string
         required: true
       description:

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.behavior.yaml

@@ -29,6 +29,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -37,13 +38,11 @@ classes:
           reference frame.
         range: SpatialSeries__data
         required: true
-        multivalued: false
+        inlined: true
       reference_frame:
         name: reference_frame
         description: Description defining what exactly 'straight-ahead' means.
         range: text
-        required: false
-        multivalued: false
     tree_root: true
   SpatialSeries__data:
     name: SpatialSeries__data
@@ -53,9 +52,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. The default
@@ -91,12 +114,19 @@ classes:
       events. BehavioralTimeSeries is for continuous data.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralEpochs)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: IntervalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: IntervalSeries
     tree_root: true
   BehavioralEvents:
     name: BehavioralEvents
@@ -104,12 +134,19 @@ classes:
       for more details.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralEvents)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   BehavioralTimeSeries:
     name: BehavioralTimeSeries
@@ -117,36 +154,57 @@ classes:
       of <a href="#BehavioralEpochs">BehavioralEpochs</a> for more details.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralTimeSeries)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   PupilTracking:
     name: PupilTracking
     description: Eye-tracking data, representing pupil size.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(PupilTracking)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   EyeTracking:
     name: EyeTracking
     description: Eye-tracking data, representing direction of gaze.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(EyeTracking)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true
   CompassDirection:
     name: CompassDirection
@@ -157,22 +215,36 @@ classes:
       be radians or degrees.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(CompassDirection)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true
   Position:
     name: Position
     description: Position data, whether along the x, x/y or x/y/z axis.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(Position)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.device.yaml

@@ -21,6 +21,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.ecephys.yaml

@@ -25,41 +25,9 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
-      data:
-        name: data
-        description: Recorded voltage data.
-        range: numeric
-        required: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_times
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_channels
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_channels
-            - alias: num_samples
-      electrodes:
-        name: electrodes
-        annotations:
-          named:
-            tag: named
-            value: true
-          source_type:
-            tag: source_type
-            value: neurodata_type_inc
-        description: DynamicTableRegion pointer to the electrodes that this time series
-          was generated from.
-        range: DynamicTableRegion
-        required: true
-        multivalued: false
       channel_conversion:
         name: channel_conversion
         description: Channel-specific conversion factor. Multiply the data in the
@@ -77,7 +45,87 @@ classes:
         range: float32
         required: false
         multivalued: false
+      data:
+        name: data
+        description: Recorded voltage data.
+        range: ElectricalSeries__data
+        required: true
+        inlined: true
+      electrodes:
+        name: electrodes
+        annotations:
+          named:
+            tag: named
+            value: true
+          source_type:
+            tag: source_type
+            value: neurodata_type_inc
+        description: DynamicTableRegion pointer to the electrodes that this time series
+          was generated from.
+        range: DynamicTableRegion
+        required: true
+        inlined: true
     tree_root: true
+  ElectricalSeries__data:
+    name: ElectricalSeries__data
+    description: Recorded voltage data.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. This value
+          is fixed to 'volts'. Actual stored values are not necessarily stored in
+          these units. To access the data in these units, multiply 'data' by 'conversion'
+          and 'channel_conversion' (if present).
+        ifabsent: string(volts)
+        range: text
+        required: true
+        equals_string: volts
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_times
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_channels
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_channels
+            - alias: num_samples
   SpikeEventSeries:
     name: SpikeEventSeries
     description: 'Stores snapshots/snippets of recorded spike events (i.e., threshold
@@ -92,24 +140,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Spike waveforms.
-        range: numeric
+        range: SpikeEventSeries__data
         required: true
-        multivalued: false
+        inlined: true
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_events
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_events
-            - alias: num_channels
-            - alias: num_samples
       timestamps:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
@@ -123,6 +162,60 @@ classes:
         required: true
         multivalued: false
     tree_root: true
+  SpikeEventSeries__data:
+    name: SpikeEventSeries__data
+    description: Spike waveforms.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement for waveforms, which is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: true
+        equals_string: volts
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_events
+            - alias: num_samples
+        - array:
+            dimensions:
+            - alias: num_events
+            - alias: num_channels
+            - alias: num_samples
   FeatureExtraction:
     name: FeatureExtraction
     description: Features, such as PC1 and PC2, that are extracted from signals stored
@@ -132,6 +225,7 @@ classes:
       name:
         name: name
         ifabsent: string(FeatureExtraction)
+        identifier: true
         range: string
         required: true
       description:
@@ -177,7 +271,7 @@ classes:
           was generated from.
         range: DynamicTableRegion
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   EventDetection:
     name: EventDetection
@@ -187,6 +281,7 @@ classes:
       name:
         name: name
         ifabsent: string(EventDetection)
+        identifier: true
         range: string
         required: true
       detection_method:
@@ -195,7 +290,6 @@ classes:
           or dV/dT threshold, as well as relevant values.
         range: text
         required: true
-        multivalued: false
       source_idx:
         name: source_idx
         description: Indices (zero-based) into source ElectricalSeries::data array
@@ -224,7 +318,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ElectricalSeries
         - range: string
@@ -236,12 +330,19 @@ classes:
       during experiment acquisition.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(EventWaveform)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpikeEventSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpikeEventSeries
     tree_root: true
   FilteredEphys:
     name: FilteredEphys
@@ -258,12 +359,19 @@ classes:
       the ElectricalSeries.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(FilteredEphys)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: ElectricalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: ElectricalSeries
     tree_root: true
   LFP:
     name: LFP
@@ -272,12 +380,19 @@ classes:
       properties should be noted in the ElectricalSeries description or comments field.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(LFP)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: ElectricalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: ElectricalSeries
     tree_root: true
   ElectrodeGroup:
     name: ElectrodeGroup
@@ -286,6 +401,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -304,8 +420,7 @@ classes:
         name: position
         description: stereotaxic or common framework coordinates
         range: ElectrodeGroup__position
-        required: false
+        inlined: true
-        multivalued: false
       device:
         name: device
         annotations:
@@ -313,7 +428,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -325,6 +440,7 @@ classes:
       name:
         name: name
         ifabsent: string(position)
+        identifier: true
         range: string
         required: true
         equals_string: position
@@ -334,24 +450,18 @@ classes:
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
       y:
         name: y
         description: y coordinate
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
       z:
         name: z
         description: z coordinate
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
   ClusterWaveforms:
     name: ClusterWaveforms
     description: DEPRECATED The mean waveform shape, including standard deviation,
@@ -365,6 +475,7 @@ classes:
       name:
         name: name
         ifabsent: string(ClusterWaveforms)
+        identifier: true
         range: string
         required: true
       waveform_filtering:
@@ -372,7 +483,6 @@ classes:
         description: Filtering applied to data before generating mean/sd
         range: text
         required: true
-        multivalued: false
       waveform_mean:
         name: waveform_mean
         description: The mean waveform for each cluster, using the same indices for
@@ -404,7 +514,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Clustering
         - range: string
@@ -418,6 +528,7 @@ classes:
       name:
         name: name
         ifabsent: string(Clustering)
+        identifier: true
         range: string
         required: true
       description:
@@ -426,7 +537,6 @@ classes:
           clusters curated using Klusters, etc)
         range: text
         required: true
-        multivalued: false
       num:
         name: num
         description: Cluster number of each event

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.epoch.yaml

@@ -22,6 +22,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       start_time:
@@ -62,14 +63,12 @@ classes:
             value: neurodata_type_inc
         description: Index for tags.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
       timeseries:
         name: timeseries
         description: An index into a TimeSeries object.
         range: TimeIntervals__timeseries
-        required: false
+        inlined: true
-        multivalued: false
       timeseries_index:
         name: timeseries_index
         annotations:
@@ -81,8 +80,7 @@ classes:
             value: neurodata_type_inc
         description: Index for timeseries.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
     tree_root: true
   TimeIntervals__timeseries:
     name: TimeIntervals__timeseries
@@ -92,6 +90,7 @@ classes:
       name:
         name: name
         ifabsent: string(timeseries)
+        identifier: true
         range: string
         required: true
         equals_string: timeseries
@@ -103,8 +102,6 @@ classes:
         array:
           exact_number_dimensions: 1
         range: int32
-        required: false
-        multivalued: false
       count:
         name: count
         description: Number of data samples available in this time series, during
@@ -112,13 +109,10 @@ classes:
         array:
           exact_number_dimensions: 1
         range: int32
-        required: false
-        multivalued: false
       timeseries:
         name: timeseries
         description: the TimeSeries that this index applies to.
         array:
           exact_number_dimensions: 1
         range: TimeSeries
-        required: false
+        inlined: true
-        multivalued: false

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.file.yaml

@@ -30,6 +30,7 @@ classes:
       name:
         name: name
         ifabsent: string(root)
+        identifier: true
         range: string
         required: true
         equals_string: root
@@ -64,13 +65,11 @@ classes:
           other files.
         range: text
         required: true
-        multivalued: false
       session_description:
         name: session_description
         description: A description of the experimental session and data in the file.
         range: text
         required: true
-        multivalued: false
       session_start_time:
         name: session_start_time
         description: 'Date and time of the experiment/session start. The date is stored
@@ -79,7 +78,6 @@ classes:
           offset. Date accuracy is up to milliseconds.'
         range: isodatetime
         required: true
-        multivalued: false
       timestamps_reference_time:
         name: timestamps_reference_time
         description: 'Date and time corresponding to time zero of all timestamps.
@@ -89,7 +87,6 @@ classes:
           times stored in the file use this time as reference (i.e., time zero).'
         range: isodatetime
         required: true
-        multivalued: false
       acquisition:
         name: acquisition
         description: Data streams recorded from the system, including ephys, ophys,
@@ -168,7 +165,8 @@ classes:
           can exist in the present file or can be linked to a remote library file.
         range: NWBFile__stimulus
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       general:
         name: general
         description: Experimental metadata, including protocol, notes and description
@@ -188,7 +186,8 @@ classes:
           should not be created unless there is data to store within them.
         range: NWBFile__general
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       intervals:
         name: intervals
         description: Experimental intervals, whether that be logically distinct sub-experiments
@@ -196,14 +195,18 @@ classes:
           an experiment, or epochs (see epochs subgroup) deriving from analysis of
           data.
         range: NWBFile__intervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       units:
         name: units
         description: Data about sorted spike units.
         range: Units
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
+      specifications:
+        name: specifications
+        description: Nested dictionary of schema specifications
+        range: dict
     tree_root: true
   NWBFile__stimulus:
     name: NWBFile__stimulus
@@ -223,6 +226,7 @@ classes:
       name:
         name: name
         ifabsent: string(stimulus)
+        identifier: true
         range: string
         required: true
         equals_string: stimulus
@@ -265,6 +269,7 @@ classes:
       name:
         name: name
         ifabsent: string(general)
+        identifier: true
         range: string
         required: true
         equals_string: general
@@ -272,14 +277,10 @@ classes:
         name: data_collection
         description: Notes about data collection and analysis.
         range: text
-        required: false
-        multivalued: false
       experiment_description:
         name: experiment_description
         description: General description of the experiment.
         range: text
-        required: false
-        multivalued: false
       experimenter:
         name: experimenter
         description: Name of person(s) who performed the experiment. Can also specify
@@ -294,8 +295,6 @@ classes:
         name: institution
         description: Institution(s) where experiment was performed.
         range: text
-        required: false
-        multivalued: false
       keywords:
         name: keywords
         description: Terms to search over.
@@ -309,28 +308,20 @@ classes:
         name: lab
         description: Laboratory where experiment was performed.
         range: text
-        required: false
-        multivalued: false
       notes:
         name: notes
         description: Notes about the experiment.
         range: text
-        required: false
-        multivalued: false
       pharmacology:
         name: pharmacology
         description: Description of drugs used, including how and when they were administered.
           Anesthesia(s), painkiller(s), etc., plus dosage, concentration, etc.
         range: text
-        required: false
-        multivalued: false
       protocol:
         name: protocol
         description: Experimental protocol, if applicable. e.g., include IACUC protocol
           number.
         range: text
-        required: false
-        multivalued: false
       related_publications:
         name: related_publications
         description: Publication information. PMID, DOI, URL, etc.
@@ -344,49 +335,39 @@ classes:
         name: session_id
         description: Lab-specific ID for the session.
         range: text
-        required: false
-        multivalued: false
       slices:
         name: slices
         description: Description of slices, including information about preparation
           thickness, orientation, temperature, and bath solution.
         range: text
-        required: false
-        multivalued: false
       source_script:
         name: source_script
         description: Script file or link to public source code used to create this
           NWB file.
         range: general__source_script
-        required: false
+        inlined: true
-        multivalued: false
       stimulus:
         name: stimulus
         description: Notes about stimuli, such as how and where they were presented.
         range: text
-        required: false
-        multivalued: false
       surgery:
         name: surgery
         description: Narrative description about surgery/surgeries, including date(s)
           and who performed surgery.
         range: text
-        required: false
-        multivalued: false
       virus:
         name: virus
         description: Information about virus(es) used in experiments, including virus
           ID, source, date made, injection location, volume, etc.
         range: text
-        required: false
-        multivalued: false
       nwb_container:
         name: nwb_container
         description: Place-holder than can be extended so that lab-specific meta-data
           can be placed in /general.
         range: NWBContainer
-        required: false
         multivalued: true
+        inlined: true
+        inlined_as_list: false
       devices:
         name: devices
         description: Description of hardware devices used during experiment, e.g.,
@@ -401,20 +382,20 @@ classes:
         description: Information about the animal or person from which the data was
           measured.
         range: Subject
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       extracellular_ephys:
         name: extracellular_ephys
         description: Metadata related to extracellular electrophysiology.
         range: general__extracellular_ephys
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       intracellular_ephys:
         name: intracellular_ephys
         description: Metadata related to intracellular electrophysiology.
         range: general__intracellular_ephys
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
       optogenetics:
         name: optogenetics
         description: Metadata describing optogenetic stimuluation.
@@ -439,6 +420,7 @@ classes:
       name:
         name: name
         ifabsent: string(source_script)
+        identifier: true
         range: string
         required: true
         equals_string: source_script
@@ -459,6 +441,7 @@ classes:
       name:
         name: name
         ifabsent: string(subject)
+        identifier: true
         range: string
         required: true
         equals_string: subject
@@ -466,52 +449,36 @@ classes:
         name: age
         description: Age of subject. Can be supplied instead of 'date_of_birth'.
         range: text
-        required: false
-        multivalued: false
       date_of_birth:
         name: date_of_birth
         description: Date of birth of subject. Can be supplied instead of 'age'.
         range: isodatetime
-        required: false
-        multivalued: false
       description:
         name: description
         description: Description of subject and where subject came from (e.g., breeder,
           if animal).
         range: text
-        required: false
-        multivalued: false
       genotype:
         name: genotype
         description: Genetic strain. If absent, assume Wild Type (WT).
         range: text
-        required: false
-        multivalued: false
       sex:
         name: sex
         description: Gender of subject.
         range: text
-        required: false
-        multivalued: false
       species:
         name: species
         description: Species of subject.
         range: text
-        required: false
-        multivalued: false
       subject_id:
         name: subject_id
         description: ID of animal/person used/participating in experiment (lab convention).
         range: text
-        required: false
-        multivalued: false
       weight:
         name: weight
         description: Weight at time of experiment, at time of surgery and at other
           important times.
         range: text
-        required: false
-        multivalued: false
   general__extracellular_ephys:
     name: general__extracellular_ephys
     description: Metadata related to extracellular electrophysiology.
@@ -519,21 +486,23 @@ classes:
       name:
         name: name
         ifabsent: string(extracellular_ephys)
+        identifier: true
         range: string
         required: true
         equals_string: extracellular_ephys
-      electrode_group:
-        name: electrode_group
-        description: Physical group of electrodes.
-        range: ElectrodeGroup
-        required: false
-        multivalued: true
       electrodes:
         name: electrodes
         description: A table of all electrodes (i.e. channels) used for recording.
         range: extracellular_ephys__electrodes
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
+      value:
+        name: value
+        description: Physical group of electrodes.
+        range: ElectrodeGroup
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
   extracellular_ephys__electrodes:
     name: extracellular_ephys__electrodes
     description: A table of all electrodes (i.e. channels) used for recording.
@@ -542,6 +511,7 @@ classes:
       name:
         name: name
         ifabsent: string(electrodes)
+        identifier: true
         range: string
         required: true
         equals_string: electrodes
@@ -604,9 +574,13 @@ classes:
       group:
         name: group
         description: Reference to the ElectrodeGroup this electrode is a part of.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
         range: ElectrodeGroup
         required: true
-        multivalued: true
+        multivalued: false
+        inlined: true
       group_name:
         name: group_name
         description: Name of the ElectrodeGroup this electrode is a part of.
@@ -659,6 +633,7 @@ classes:
       name:
         name: name
         ifabsent: string(intracellular_ephys)
+        identifier: true
         range: string
         required: true
         equals_string: intracellular_ephys
@@ -668,20 +643,19 @@ classes:
           frequency fall-off, etc. If this changes between TimeSeries, filter description
           should be stored as a text attribute for each TimeSeries.
         range: text
-        required: false
-        multivalued: false
-      intracellular_electrode:
-        name: intracellular_electrode
-        description: An intracellular electrode.
-        range: IntracellularElectrode
-        required: false
-        multivalued: true
       sweep_table:
         name: sweep_table
         description: The table which groups different PatchClampSeries together.
         range: SweepTable
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
+      value:
+        name: value
+        description: An intracellular electrode.
+        range: IntracellularElectrode
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
   NWBFile__intervals:
     name: NWBFile__intervals
     description: Experimental intervals, whether that be logically distinct sub-experiments
@@ -691,6 +665,7 @@ classes:
       name:
         name: name
         ifabsent: string(intervals)
+        identifier: true
         range: string
         required: true
         equals_string: intervals
@@ -699,24 +674,25 @@ classes:
         description: Divisions in time marking experimental stages or sub-divisions
           of a single recording session.
         range: TimeIntervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
       trials:
         name: trials
         description: Repeated experimental events that have a logical grouping.
         range: TimeIntervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
       invalid_times:
         name: invalid_times
         description: Time intervals that should be removed from analysis.
         range: TimeIntervals
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: false
-      time_intervals:
+      value:
-        name: time_intervals
+        name: value
         description: Optional additional table(s) for describing other experimental
           time intervals.
         range: TimeIntervals
-        required: false
         multivalued: true
+        inlined: true
+        inlined_as_list: false

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.icephys.yaml

@@ -23,6 +23,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       stimulus_description:
@@ -40,14 +41,12 @@ classes:
         description: Recorded voltage or current.
         range: PatchClampSeries__data
         required: true
-        multivalued: false
+        inlined: true
       gain:
         name: gain
         description: Gain of the recording, in units Volt/Amp (v-clamp) or Volt/Volt
           (c-clamp).
         range: float32
-        required: false
-        multivalued: false
       electrode:
         name: electrode
         annotations:
@@ -55,7 +54,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: IntracellularElectrode
         - range: string
@@ -67,9 +66,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. Actual stored
@@ -92,32 +115,27 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
+      bias_current:
+        name: bias_current
+        description: Bias current, in amps.
+        range: float32
+      bridge_balance:
+        name: bridge_balance
+        description: Bridge balance, in ohms.
+        range: float32
+      capacitance_compensation:
+        name: capacitance_compensation
+        description: Capacitance compensation, in farads.
+        range: float32
       data:
         name: data
         description: Recorded voltage.
         range: CurrentClampSeries__data
         required: true
-        multivalued: false
+        inlined: true
-      bias_current:
-        name: bias_current
-        description: Bias current, in amps.
-        range: float32
-        required: false
-        multivalued: false
-      bridge_balance:
-        name: bridge_balance
-        description: Bridge balance, in ohms.
-        range: float32
-        required: false
-        multivalued: false
-      capacitance_compensation:
-        name: capacitance_compensation
-        description: Capacitance compensation, in farads.
-        range: float32
-        required: false
-        multivalued: false
     tree_root: true
   CurrentClampSeries__data:
     name: CurrentClampSeries__data
@@ -126,9 +144,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -140,8 +182,10 @@ classes:
         equals_string: volts
       value:
         name: value
-        range: AnyType
+        array:
-        required: true
+          dimensions:
+          - alias: num_times
+        range: numeric
   IZeroClampSeries:
     name: IZeroClampSeries
     description: Voltage data from an intracellular recording when all current and
@@ -152,6 +196,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       bias_current:
@@ -159,19 +204,16 @@ classes:
         description: Bias current, in amps, fixed to 0.0.
         range: float32
         required: true
-        multivalued: false
       bridge_balance:
         name: bridge_balance
         description: Bridge balance, in ohms, fixed to 0.0.
         range: float32
         required: true
-        multivalued: false
       capacitance_compensation:
         name: capacitance_compensation
         description: Capacitance compensation, in farads, fixed to 0.0.
         range: float32
         required: true
-        multivalued: false
     tree_root: true
   CurrentClampStimulusSeries:
     name: CurrentClampStimulusSeries
@@ -180,6 +222,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -187,7 +230,7 @@ classes:
         description: Stimulus current applied.
         range: CurrentClampStimulusSeries__data
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   CurrentClampStimulusSeries__data:
     name: CurrentClampStimulusSeries__data
@@ -196,9 +239,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -210,8 +277,10 @@ classes:
         equals_string: amperes
       value:
         name: value
-        range: AnyType
+        array:
-        required: true
+          dimensions:
+          - alias: num_times
+        range: numeric
   VoltageClampSeries:
     name: VoltageClampSeries
     description: Current data from an intracellular voltage-clamp recording. A corresponding
@@ -221,80 +290,51 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
+      capacitance_fast:
+        name: capacitance_fast
+        description: Fast capacitance, in farads.
+        range: VoltageClampSeries__capacitance_fast
+        inlined: true
+      capacitance_slow:
+        name: capacitance_slow
+        description: Slow capacitance, in farads.
+        range: VoltageClampSeries__capacitance_slow
+        inlined: true
       data:
         name: data
         description: Recorded current.
         range: VoltageClampSeries__data
         required: true
-        multivalued: false
+        inlined: true
-      capacitance_fast:
-        name: capacitance_fast
-        description: Fast capacitance, in farads.
-        range: VoltageClampSeries__capacitance_fast
-        required: false
-        multivalued: false
-      capacitance_slow:
-        name: capacitance_slow
-        description: Slow capacitance, in farads.
-        range: VoltageClampSeries__capacitance_slow
-        required: false
-        multivalued: false
       resistance_comp_bandwidth:
         name: resistance_comp_bandwidth
         description: Resistance compensation bandwidth, in hertz.
         range: VoltageClampSeries__resistance_comp_bandwidth
-        required: false
+        inlined: true
-        multivalued: false
       resistance_comp_correction:
         name: resistance_comp_correction
         description: Resistance compensation correction, in percent.
         range: VoltageClampSeries__resistance_comp_correction
-        required: false
+        inlined: true
-        multivalued: false
       resistance_comp_prediction:
         name: resistance_comp_prediction
         description: Resistance compensation prediction, in percent.
         range: VoltageClampSeries__resistance_comp_prediction
-        required: false
+        inlined: true
-        multivalued: false
       whole_cell_capacitance_comp:
         name: whole_cell_capacitance_comp
         description: Whole cell capacitance compensation, in farads.
         range: VoltageClampSeries__whole_cell_capacitance_comp
-        required: false
+        inlined: true
-        multivalued: false
       whole_cell_series_resistance_comp:
         name: whole_cell_series_resistance_comp
         description: Whole cell series resistance compensation, in ohms.
         range: VoltageClampSeries__whole_cell_series_resistance_comp
-        required: false
+        inlined: true
-        multivalued: false
     tree_root: true
-  VoltageClampSeries__data:
-    name: VoltageClampSeries__data
-    description: Recorded current.
-    attributes:
-      name:
-        name: name
-        ifabsent: string(data)
-        range: string
-        required: true
-        equals_string: data
-      unit:
-        name: unit
-        description: Base unit of measurement for working with the data. which is
-          fixed to 'amperes'. Actual stored values are not necessarily stored in these
-          units. To access the data in these units, multiply 'data' by 'conversion'.
-        ifabsent: string(amperes)
-        range: text
-        required: true
-        equals_string: amperes
-      value:
-        name: value
-        range: AnyType
-        required: true
   VoltageClampSeries__capacitance_fast:
     name: VoltageClampSeries__capacitance_fast
     description: Fast capacitance, in farads.
@@ -302,6 +342,7 @@ classes:
       name:
         name: name
         ifabsent: string(capacitance_fast)
+        identifier: true
         range: string
         required: true
         equals_string: capacitance_fast
@@ -323,6 +364,7 @@ classes:
       name:
         name: name
         ifabsent: string(capacitance_slow)
+        identifier: true
         range: string
         required: true
         equals_string: capacitance_slow
@@ -337,6 +379,55 @@ classes:
         name: value
         range: float32
         required: true
+  VoltageClampSeries__data:
+    name: VoltageClampSeries__data
+    description: Recorded current.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. which is
+          fixed to 'amperes'. Actual stored values are not necessarily stored in these
+          units. To access the data in these units, multiply 'data' by 'conversion'.
+        ifabsent: string(amperes)
+        range: text
+        required: true
+        equals_string: amperes
+      value:
+        name: value
+        array:
+          dimensions:
+          - alias: num_times
+        range: numeric
   VoltageClampSeries__resistance_comp_bandwidth:
     name: VoltageClampSeries__resistance_comp_bandwidth
     description: Resistance compensation bandwidth, in hertz.
@@ -344,6 +435,7 @@ classes:
       name:
         name: name
         ifabsent: string(resistance_comp_bandwidth)
+        identifier: true
         range: string
         required: true
         equals_string: resistance_comp_bandwidth
@@ -366,6 +458,7 @@ classes:
       name:
         name: name
         ifabsent: string(resistance_comp_correction)
+        identifier: true
         range: string
         required: true
         equals_string: resistance_comp_correction
@@ -388,6 +481,7 @@ classes:
       name:
         name: name
         ifabsent: string(resistance_comp_prediction)
+        identifier: true
         range: string
         required: true
         equals_string: resistance_comp_prediction
@@ -410,6 +504,7 @@ classes:
       name:
         name: name
         ifabsent: string(whole_cell_capacitance_comp)
+        identifier: true
         range: string
         required: true
         equals_string: whole_cell_capacitance_comp
@@ -432,6 +527,7 @@ classes:
       name:
         name: name
         ifabsent: string(whole_cell_series_resistance_comp)
+        identifier: true
         range: string
         required: true
         equals_string: whole_cell_series_resistance_comp
@@ -454,6 +550,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -461,7 +558,7 @@ classes:
         description: Stimulus voltage applied.
         range: VoltageClampStimulusSeries__data
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   VoltageClampStimulusSeries__data:
     name: VoltageClampStimulusSeries__data
@@ -470,9 +567,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. which is
@@ -484,8 +605,10 @@ classes:
         equals_string: volts
       value:
         name: value
-        range: AnyType
+        array:
-        required: true
+          dimensions:
+          - alias: num_times
+        range: numeric
   IntracellularElectrode:
     name: IntracellularElectrode
     description: An intracellular electrode and its metadata.
@@ -493,6 +616,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -500,45 +624,32 @@ classes:
         description: Description of electrode (e.g.,  whole-cell, sharp, etc.).
         range: text
         required: true
-        multivalued: false
       filtering:
         name: filtering
         description: Electrode specific filtering.
         range: text
-        required: false
-        multivalued: false
       initial_access_resistance:
         name: initial_access_resistance
         description: Initial access resistance.
         range: text
-        required: false
-        multivalued: false
       location:
         name: location
         description: Location of the electrode. Specify the area, layer, comments
           on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use
           standard atlas names for anatomical regions when possible.
         range: text
-        required: false
-        multivalued: false
       resistance:
         name: resistance
         description: Electrode resistance, in ohms.
         range: text
-        required: false
-        multivalued: false
       seal:
         name: seal
         description: Information about seal used for recording.
         range: text
-        required: false
-        multivalued: false
       slice:
         name: slice
         description: Information about slice used for recording.
         range: text
-        required: false
-        multivalued: false
       device:
         name: device
         annotations:
@@ -546,7 +657,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -558,23 +669,19 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
-      sweep_number:
-        name: sweep_number
-        description: Sweep number of the PatchClampSeries in that row.
-        array:
-          minimum_number_dimensions: 1
-          maximum_number_dimensions: false
-        range: uint32
-        required: true
-        multivalued: false
       series:
         name: series
         description: The PatchClampSeries with the sweep number in that row.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
         range: PatchClampSeries
         required: true
-        multivalued: true
+        multivalued: false
+        inlined: true
       series_index:
         name: series_index
         annotations:
@@ -587,5 +694,14 @@ classes:
         description: Index for series.
         range: VectorIndex
         required: true
+        inlined: true
+      sweep_number:
+        name: sweep_number
+        description: Sweep number of the PatchClampSeries in that row.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
+        range: uint32
+        required: true
         multivalued: false
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.image.yaml

@@ -20,6 +20,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       value:
@@ -37,6 +38,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       value:
@@ -56,6 +58,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       value:
@@ -80,26 +83,14 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Binary data representing images across frames.
-        range: numeric
+        range: ImageSeries__data
-        required: false
+        inlined: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: frame
-            - alias: x
-            - alias: y
-        - array:
-            dimensions:
-            - alias: frame
-            - alias: x
-            - alias: y
-            - alias: z
       dimension:
         name: dimension
         description: Number of pixels on x, y, (and z) axes.
@@ -117,18 +108,72 @@ classes:
           used if the image is stored in another NWB file and that file is linked
           to this file.
         range: ImageSeries__external_file
-        required: false
+        inlined: true
-        multivalued: false
       format:
         name: format
         description: Format of image. If this is 'external', then the attribute 'external_file'
           contains the path information to the image files. If this is 'raw', then
           the raw (single-channel) binary data is stored in the 'data' dataset. If
           this attribute is not present, then the default format='raw' case is assumed.
+        ifabsent: string(raw)
         range: text
-        required: false
-        multivalued: false
     tree_root: true
+  ImageSeries__data:
+    name: ImageSeries__data
+    description: Binary data representing images across frames.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Actual stored
+          values are not necessarily stored in these units. To access the data in
+          these units, multiply 'data' by 'conversion'.
+        range: text
+        required: true
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: frame
+            - alias: x
+            - alias: y
+        - array:
+            dimensions:
+            - alias: frame
+            - alias: x
+            - alias: y
+            - alias: z
   ImageSeries__external_file:
     name: ImageSeries__external_file
     description: Paths to one or more external file(s). The field is only present
@@ -139,6 +184,7 @@ classes:
       name:
         name: name
         ifabsent: string(external_file)
+        identifier: true
         range: string
         required: true
         equals_string: external_file
@@ -176,6 +222,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       masked_imageseries:
@@ -185,7 +232,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ImageSeries
         - range: string
@@ -201,14 +248,13 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       distance:
         name: distance
         description: Distance from camera/monitor to target/eye.
         range: float32
-        required: false
-        multivalued: false
       field_of_view:
         name: field_of_view
         description: Width, height and depth of image, or imaged area, in meters.
@@ -229,8 +275,6 @@ classes:
         description: Description of image relative to some reference frame (e.g.,
           which way is up). Must also specify frame of reference.
         range: text
-        required: false
-        multivalued: false
     tree_root: true
   IndexSeries:
     name: IndexSeries
@@ -244,17 +288,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Index of the frame in the referenced ImageSeries.
-        array:
+        range: IndexSeries__data
-          dimensions:
-          - alias: num_times
-        range: int32
         required: true
-        multivalued: false
+        inlined: true
       indexed_timeseries:
         name: indexed_timeseries
         annotations:
@@ -262,8 +304,55 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ImageSeries
         - range: string
     tree_root: true
+  IndexSeries__data:
+    name: IndexSeries__data
+    description: Index of the frame in the referenced ImageSeries.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Actual stored
+          values are not necessarily stored in these units. To access the data in
+          these units, multiply 'data' by 'conversion'.
+        range: text
+        required: true
+      value:
+        name: value
+        array:
+          dimensions:
+          - alias: num_times
+        range: int32

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.language.yaml

@@ -66,6 +66,7 @@ types:
   numeric:
     name: numeric
     typeof: float
+    repr: float | int
   text:
     name: text
     typeof: string
@@ -87,6 +88,9 @@ types:
   isodatetime:
     name: isodatetime
     typeof: datetime
+  dict:
+    name: dict
+    repr: dict
 classes:
   AnyType:
     name: AnyType

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.misc.yaml

@@ -30,6 +30,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -37,7 +38,7 @@ classes:
         description: Values of each feature at each time.
         range: AbstractFeatureSeries__data
         required: true
-        multivalued: false
+        inlined: true
       feature_units:
         name: feature_units
         description: Units of each feature.
@@ -64,9 +65,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Since there can be different units for different features, store
@@ -96,18 +121,63 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Annotations made during an experiment.
+        range: AnnotationSeries__data
+        required: true
+        inlined: true
+    tree_root: true
+  AnnotationSeries__data:
+    name: AnnotationSeries__data
+    description: Annotations made during an experiment.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data. Annotations
+          have no units, so the value is fixed to -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: true
+        equals_number: -1
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Annotations
+          have no units, so the value is fixed to 'n/a'.
+        ifabsent: string(n/a)
+        range: text
+        required: true
+        equals_string: n/a
+      value:
+        name: value
         array:
           dimensions:
           - alias: num_times
         range: text
-        required: true
-        multivalued: false
-    tree_root: true
   IntervalSeries:
     name: IntervalSeries
     description: Stores intervals of data. The timestamps field stores the beginning
@@ -121,18 +191,63 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Use values >0 if interval started, <0 if interval ended.
+        range: IntervalSeries__data
+        required: true
+        inlined: true
+    tree_root: true
+  IntervalSeries__data:
+    name: IntervalSeries__data
+    description: Use values >0 if interval started, <0 if interval ended.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data. Annotations
+          have no units, so the value is fixed to -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: true
+        equals_number: -1
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Annotations
+          have no units, so the value is fixed to 'n/a'.
+        ifabsent: string(n/a)
+        range: text
+        required: true
+        equals_string: n/a
+      value:
+        name: value
         array:
           dimensions:
           - alias: num_times
         range: int8
-        required: true
-        multivalued: false
-    tree_root: true
   DecompositionSeries:
     name: DecompositionSeries
     description: Spectral analysis of a time series, e.g. of an LFP or a speech signal.
@@ -140,6 +255,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -147,28 +263,27 @@ classes:
         description: Data decomposed into frequency bands.
         range: DecompositionSeries__data
         required: true
-        multivalued: false
+        inlined: true
       metric:
         name: metric
         description: The metric used, e.g. phase, amplitude, power.
         range: text
         required: true
-        multivalued: false
       bands:
         name: bands
         description: Table for describing the bands that this series was generated
           from. There should be one row in this table for each band.
         range: DecompositionSeries__bands
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       source_timeseries:
         name: source_timeseries
         annotations:
           source_type:
             tag: source_type
             value: link
-        required: false
+        inlined: true
-        multivalued: false
         any_of:
         - range: TimeSeries
         - range: string
@@ -180,9 +295,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. Actual stored
@@ -208,6 +347,7 @@ classes:
       name:
         name: name
         ifabsent: string(bands)
+        identifier: true
         range: string
         required: true
         equals_string: bands
@@ -259,10 +399,21 @@ classes:
       name:
         name: name
         ifabsent: string(Units)
+        identifier: true
         range: string
         required: true
-      spike_times_index:
+      electrode_group:
-        name: spike_times_index
+        name: electrode_group
+        description: Electrode group that each spike unit came from.
+        array:
+          minimum_number_dimensions: 1
+          maximum_number_dimensions: false
+        range: ElectrodeGroup
+        required: false
+        multivalued: false
+        inlined: true
+      electrodes:
+        name: electrodes
         annotations:
           named:
             tag: named
@@ -270,14 +421,30 @@ classes:
           source_type:
             tag: source_type
             value: neurodata_type_inc
-        description: Index into the spike_times dataset.
+        description: Electrode that each spike unit came from, specified using a DynamicTableRegion.
+        range: DynamicTableRegion
+        inlined: true
+      electrodes_index:
+        name: electrodes_index
+        annotations:
+          named:
+            tag: named
+            value: true
+          source_type:
+            tag: source_type
+            value: neurodata_type_inc
+        description: Index into electrodes.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
+      obs_intervals:
-      spike_times:
+        name: obs_intervals
-        name: spike_times
+        description: Observation intervals for each unit.
-        description: Spike times for each unit.
+        array:
-        range: Units__spike_times
+          dimensions:
+          - alias: num_intervals
+          - alias: start_end
+            exact_cardinality: 2
+        range: float64
         required: false
         multivalued: false
       obs_intervals_index:
@@ -291,21 +458,14 @@ classes:
             value: neurodata_type_inc
         description: Index into the obs_intervals dataset.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
+      spike_times:
-      obs_intervals:
+        name: spike_times
-        name: obs_intervals
+        description: Spike times for each unit.
-        description: Observation intervals for each unit.
+        range: Units__spike_times
-        array:
+        inlined: true
-          dimensions:
+      spike_times_index:
-          - alias: num_intervals
+        name: spike_times_index
-          - alias: start_end
-            exact_cardinality: 2
-        range: float64
-        required: false
-        multivalued: false
-      electrodes_index:
-        name: electrodes_index
         annotations:
           named:
             tag: named
@@ -313,61 +473,19 @@ classes:
           source_type:
             tag: source_type
             value: neurodata_type_inc
-        description: Index into electrodes.
+        description: Index into the spike_times dataset.
         range: VectorIndex
-        required: false
+        inlined: true
-        multivalued: false
-      electrodes:
-        name: electrodes
-        annotations:
-          named:
-            tag: named
-            value: true
-          source_type:
-            tag: source_type
-            value: neurodata_type_inc
-        description: Electrode that each spike unit came from, specified using a DynamicTableRegion.
-        range: DynamicTableRegion
-        required: false
-        multivalued: false
-      electrode_group:
-        name: electrode_group
-        description: Electrode group that each spike unit came from.
-        range: ElectrodeGroup
-        required: false
-        multivalued: true
       waveform_mean:
         name: waveform_mean
         description: Spike waveform mean for each spike unit.
-        range: float32
+        range: Units__waveform_mean
-        required: false
+        inlined: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-            - alias: num_electrodes
       waveform_sd:
         name: waveform_sd
         description: Spike waveform standard deviation for each spike unit.
-        range: float32
+        range: Units__waveform_sd
-        required: false
+        inlined: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_units
-            - alias: num_samples
-            - alias: num_electrodes
     tree_root: true
   Units__spike_times:
     name: Units__spike_times
@@ -377,6 +495,7 @@ classes:
       name:
         name: name
         ifabsent: string(spike_times)
+        identifier: true
         range: string
         required: true
         equals_string: spike_times
@@ -389,3 +508,51 @@ classes:
           for the spike time to be between samples.
         range: float64
         required: false
+  Units__waveform_mean:
+    name: Units__waveform_mean
+    description: Spike waveform mean for each spike unit.
+    is_a: VectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_mean)
+        identifier: true
+        range: string
+        required: true
+        equals_string: waveform_mean
+      sampling_rate:
+        name: sampling_rate
+        description: Sampling rate, in hertz.
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement. This value is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: false
+        equals_string: volts
+  Units__waveform_sd:
+    name: Units__waveform_sd
+    description: Spike waveform standard deviation for each spike unit.
+    is_a: VectorData
+    attributes:
+      name:
+        name: name
+        ifabsent: string(waveform_sd)
+        identifier: true
+        range: string
+        required: true
+        equals_string: waveform_sd
+      sampling_rate:
+        name: sampling_rate
+        description: Sampling rate, in hertz.
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement. This value is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: false
+        equals_string: volts

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.ogen.yaml

@@ -21,17 +21,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Applied power for optogenetic stimulus, in watts.
-        array:
+        range: OptogeneticSeries__data
-          dimensions:
-          - alias: num_times
-        range: numeric
         required: true
-        multivalued: false
+        inlined: true
       site:
         name: site
         annotations:
@@ -39,11 +37,58 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: OptogeneticStimulusSite
         - range: string
     tree_root: true
+  OptogeneticSeries__data:
+    name: OptogeneticSeries__data
+    description: Applied power for optogenetic stimulus, in watts.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement for data, which is fixed to 'watts'.
+        ifabsent: string(watts)
+        range: text
+        required: true
+        equals_string: watts
+      value:
+        name: value
+        array:
+          dimensions:
+          - alias: num_times
+        range: numeric
   OptogeneticStimulusSite:
     name: OptogeneticStimulusSite
     description: A site of optogenetic stimulation.
@@ -51,6 +96,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -58,13 +104,11 @@ classes:
         description: Description of stimulation site.
         range: text
         required: true
-        multivalued: false
       excitation_lambda:
         name: excitation_lambda
         description: Excitation wavelength, in nm.
         range: float32
         required: true
-        multivalued: false
       location:
         name: location
         description: Location of the stimulation site. Specify the area, layer, comments
@@ -72,7 +116,6 @@ classes:
           standard atlas names for anatomical regions when possible.
         range: text
         required: true
-        multivalued: false
       device:
         name: device
         annotations:
@@ -80,7 +123,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.ophys.yaml

@@ -23,6 +23,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       pmt_gain:
@@ -59,7 +60,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ImagingPlane
         - range: string
@@ -72,22 +73,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Signals from ROIs.
-        range: numeric
+        range: RoiResponseSeries__data
         required: true
-        multivalued: false
+        inlined: true
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_times
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_rois
       rois:
         name: rois
         annotations:
@@ -101,8 +95,60 @@ classes:
           on the ROIs stored in this timeseries.
         range: DynamicTableRegion
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
+  RoiResponseSeries__data:
+    name: RoiResponseSeries__data
+    description: Signals from ROIs.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. Actual stored
+          values are not necessarily stored in these units. To access the data in
+          these units, multiply 'data' by 'conversion'.
+        range: text
+        required: true
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_times
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_rois
   DfOverF:
     name: DfOverF
     description: dF/F information about a region of interest (ROI). Storage hierarchy
@@ -110,12 +156,19 @@ classes:
       for image planes).
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(DfOverF)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: RoiResponseSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: RoiResponseSeries
     tree_root: true
   Fluorescence:
     name: Fluorescence
@@ -124,12 +177,19 @@ classes:
       for ROIs and for image planes).
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(Fluorescence)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: RoiResponseSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: RoiResponseSeries
     tree_root: true
   ImageSegmentation:
     name: ImageSegmentation
@@ -142,12 +202,19 @@ classes:
       is required and ROI names should remain consistent between them.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(ImageSegmentation)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: DynamicTable
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: DynamicTable
     tree_root: true
   ImagingPlane:
     name: ImagingPlane
@@ -156,32 +223,28 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
         name: description
         description: Description of the imaging plane.
         range: text
-        required: false
-        multivalued: false
       excitation_lambda:
         name: excitation_lambda
         description: Excitation wavelength, in nm.
         range: float32
         required: true
-        multivalued: false
       imaging_rate:
         name: imaging_rate
         description: Rate that images are acquired, in Hz.
         range: float32
         required: true
-        multivalued: false
       indicator:
         name: indicator
         description: Calcium indicator.
         range: text
         required: true
-        multivalued: false
       location:
         name: location
         description: Location of the imaging plane. Specify the area, layer, comments
@@ -189,31 +252,27 @@ classes:
           standard atlas names for anatomical regions when possible.
         range: text
         required: true
-        multivalued: false
       manifold:
         name: manifold
         description: DEPRECATED Physical position of each pixel. 'xyz' represents
           the position of the pixel relative to the defined coordinate space. Deprecated
           in favor of origin_coords and grid_spacing.
         range: ImagingPlane__manifold
-        required: false
+        inlined: true
-        multivalued: false
       origin_coords:
         name: origin_coords
         description: Physical location of the first element of the imaging plane (0,
           0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for
           what the physical location is relative to (e.g., bregma).
         range: ImagingPlane__origin_coords
-        required: false
+        inlined: true
-        multivalued: false
       grid_spacing:
         name: grid_spacing
         description: Space between pixels in (x, y) or voxels in (x, y, z) directions,
           in the specified unit. Assumes imaging plane is a regular grid. See also
           reference_frame to interpret the grid.
         range: ImagingPlane__grid_spacing
-        required: false
+        inlined: true
-        multivalued: false
       reference_frame:
         name: reference_frame
         description: Describes reference frame of origin_coords and grid_spacing.
@@ -234,14 +293,13 @@ classes:
           axis (larger index = more rightward). Third dimension corresponds to dorsal-ventral
           axis (larger index = more ventral)."
         range: text
-        required: false
-        multivalued: false
       optical_channel:
         name: optical_channel
         description: An optical channel used to record from an imaging plane.
         range: OpticalChannel
         required: true
-        multivalued: false
+        inlined: true
+        inlined_as_list: true
       device:
         name: device
         annotations:
@@ -249,7 +307,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -263,6 +321,7 @@ classes:
       name:
         name: name
         ifabsent: string(manifold)
+        identifier: true
         range: string
         required: true
         equals_string: manifold
@@ -312,6 +371,7 @@ classes:
       name:
         name: name
         ifabsent: string(origin_coords)
+        identifier: true
         range: string
         required: true
         equals_string: origin_coords
@@ -339,6 +399,7 @@ classes:
       name:
         name: name
         ifabsent: string(grid_spacing)
+        identifier: true
         range: string
         required: true
         equals_string: grid_spacing
@@ -364,6 +425,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -371,13 +433,11 @@ classes:
         description: Description or other notes about the channel.
         range: text
         required: true
-        multivalued: false
       emission_lambda:
         name: emission_lambda
         description: Emission wavelength for channel, in nm.
         range: float32
         required: true
-        multivalued: false
   MotionCorrection:
     name: MotionCorrection
     description: 'An image stack where all frames are shifted (registered) to a common
@@ -385,10 +445,17 @@ classes:
       frame at each point in time is assumed to be 2-D (has only x & y dimensions).'
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(MotionCorrection)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: NWBDataInterface
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: NWBDataInterface
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_1/core.nwb.retinotopy.yaml

@@ -21,6 +21,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       dimension:
@@ -52,6 +53,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       unit:
@@ -75,6 +77,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       bits_per_pixel:
@@ -115,6 +118,7 @@ classes:
       name:
         name: name
         ifabsent: string(ImagingRetinotopy)
+        identifier: true
         range: string
         required: true
       axis_1_phase_map:
@@ -129,7 +133,7 @@ classes:
         description: Phase response to stimulus on the first measured axis.
         range: AxisMap
         required: true
-        multivalued: false
+        inlined: true
       axis_1_power_map:
         name: axis_1_power_map
         annotations:
@@ -142,8 +146,7 @@ classes:
         description: Power response on the first measured axis. Response is scaled
           so 0.0 is no power in the response and 1.0 is maximum relative power.
         range: AxisMap
-        required: false
+        inlined: true
-        multivalued: false
       axis_2_phase_map:
         name: axis_2_phase_map
         annotations:
@@ -156,7 +159,7 @@ classes:
         description: Phase response to stimulus on the second measured axis.
         range: AxisMap
         required: true
-        multivalued: false
+        inlined: true
       axis_2_power_map:
         name: axis_2_power_map
         annotations:
@@ -168,8 +171,7 @@ classes:
             value: neurodata_type_inc
         description: Power response to stimulus on the second measured axis.
         range: AxisMap
-        required: false
+        inlined: true
-        multivalued: false
       sign_map:
         name: sign_map
         annotations:
@@ -183,7 +185,7 @@ classes:
           and axis_2.
         range: RetinotopyMap
         required: true
-        multivalued: false
+        inlined: true
       axis_descriptions:
         name: axis_descriptions
         description: Two-element array describing the contents of the two response
@@ -202,7 +204,7 @@ classes:
           focal depth, wavelength) as data collection. Array format: [rows][columns].'
         range: ImagingRetinotopy__focal_depth_image
         required: true
-        multivalued: false
+        inlined: true
       vasculature_image:
         name: vasculature_image
         annotations:
@@ -216,7 +218,7 @@ classes:
           [rows][columns]'
         range: RetinotopyImage
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   ImagingRetinotopy__focal_depth_image:
     name: ImagingRetinotopy__focal_depth_image
@@ -227,6 +229,7 @@ classes:
       name:
         name: name
         ifabsent: string(focal_depth_image)
+        identifier: true
         range: string
         required: true
         equals_string: focal_depth_image

nwb_models/src/nwb_models/schema/linkml/core/v2_2_2/core.nwb.base.yaml

@@ -20,6 +20,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -32,6 +33,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       resolution:
@@ -73,6 +75,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -84,6 +87,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
     tree_root: true
@@ -94,6 +98,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -118,15 +123,14 @@ classes:
           external file.
         range: TimeSeries__data
         required: true
-        multivalued: false
+        inlined: true
       starting_time:
         name: starting_time
         description: Timestamp of the first sample in seconds. When timestamps are
           uniformly spaced, the timestamp of the first sample can be specified and
           all subsequent ones calculated from the sampling rate attribute.
         range: TimeSeries__starting_time
-        required: false
+        inlined: true
-        multivalued: false
       timestamps:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
@@ -168,8 +172,8 @@ classes:
           external to the NWB file, in files storing raw data. Once timestamp data
           is calculated, the contents of 'sync' are mostly for archival purposes.
         range: TimeSeries__sync
-        required: false
+        inlined: true
-        multivalued: false
+        inlined_as_list: true
     tree_root: true
   TimeSeries__data:
     name: TimeSeries__data
@@ -180,6 +184,7 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
@@ -244,6 +249,7 @@ classes:
       name:
         name: name
         ifabsent: string(starting_time)
+        identifier: true
         range: string
         required: true
         equals_string: starting_time
@@ -275,6 +281,7 @@ classes:
       name:
         name: name
         ifabsent: string(sync)
+        identifier: true
         range: string
         required: true
         equals_string: sync
@@ -283,13 +290,24 @@ classes:
     description: A collection of processed data.
     is_a: NWBContainer
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        identifier: true
-      inlined_as_list: false
+        range: string
-      any_of:
+        required: true
-      - range: NWBDataInterface
+      description:
-      - range: DynamicTable
+        name: description
+        description: Description of this collection of processed data.
+        range: text
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: NWBDataInterface
+        - range: DynamicTable
     tree_root: true
   Images:
     name: Images
@@ -299,6 +317,7 @@ classes:
       name:
         name: name
         ifabsent: string(Images)
+        identifier: true
         range: string
         required: true
       description:

nwb_models/src/nwb_models/schema/linkml/core/v2_2_2/core.nwb.behavior.yaml

@@ -29,6 +29,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
@@ -37,13 +38,11 @@ classes:
           reference frame.
         range: SpatialSeries__data
         required: true
-        multivalued: false
+        inlined: true
       reference_frame:
         name: reference_frame
         description: Description defining what exactly 'straight-ahead' means.
         range: text
-        required: false
-        multivalued: false
     tree_root: true
   SpatialSeries__data:
     name: SpatialSeries__data
@@ -53,9 +52,33 @@ classes:
       name:
         name: name
         ifabsent: string(data)
+        identifier: true
         range: string
         required: true
         equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
       unit:
         name: unit
         description: Base unit of measurement for working with the data. The default
@@ -91,12 +114,19 @@ classes:
       events. BehavioralTimeSeries is for continuous data.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralEpochs)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: IntervalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: IntervalSeries
     tree_root: true
   BehavioralEvents:
     name: BehavioralEvents
@@ -104,12 +134,19 @@ classes:
       for more details.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralEvents)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   BehavioralTimeSeries:
     name: BehavioralTimeSeries
@@ -117,36 +154,57 @@ classes:
       of <a href="#BehavioralEpochs">BehavioralEpochs</a> for more details.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(BehavioralTimeSeries)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   PupilTracking:
     name: PupilTracking
     description: Eye-tracking data, representing pupil size.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(PupilTracking)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: TimeSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: TimeSeries
     tree_root: true
   EyeTracking:
     name: EyeTracking
     description: Eye-tracking data, representing direction of gaze.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(EyeTracking)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true
   CompassDirection:
     name: CompassDirection
@@ -157,22 +215,36 @@ classes:
       be radians or degrees.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(CompassDirection)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true
   Position:
     name: Position
     description: Position data, whether along the x, x/y or x/y/z axis.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(Position)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpatialSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpatialSeries
     tree_root: true

nwb_models/src/nwb_models/schema/linkml/core/v2_2_2/core.nwb.device.yaml

@@ -21,6 +21,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:

nwb_models/src/nwb_models/schema/linkml/core/v2_2_2/core.nwb.ecephys.yaml

@@ -25,41 +25,9 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
-      data:
-        name: data
-        description: Recorded voltage data.
-        range: numeric
-        required: true
-        multivalued: false
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_times
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_channels
-        - array:
-            dimensions:
-            - alias: num_times
-            - alias: num_channels
-            - alias: num_samples
-      electrodes:
-        name: electrodes
-        annotations:
-          named:
-            tag: named
-            value: true
-          source_type:
-            tag: source_type
-            value: neurodata_type_inc
-        description: DynamicTableRegion pointer to the electrodes that this time series
-          was generated from.
-        range: DynamicTableRegion
-        required: true
-        multivalued: false
       channel_conversion:
         name: channel_conversion
         description: Channel-specific conversion factor. Multiply the data in the
@@ -77,7 +45,87 @@ classes:
         range: float32
         required: false
         multivalued: false
+      data:
+        name: data
+        description: Recorded voltage data.
+        range: ElectricalSeries__data
+        required: true
+        inlined: true
+      electrodes:
+        name: electrodes
+        annotations:
+          named:
+            tag: named
+            value: true
+          source_type:
+            tag: source_type
+            value: neurodata_type_inc
+        description: DynamicTableRegion pointer to the electrodes that this time series
+          was generated from.
+        range: DynamicTableRegion
+        required: true
+        inlined: true
     tree_root: true
+  ElectricalSeries__data:
+    name: ElectricalSeries__data
+    description: Recorded voltage data.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Base unit of measurement for working with the data. This value
+          is fixed to 'volts'. Actual stored values are not necessarily stored in
+          these units. To access the data in these units, multiply 'data' by 'conversion'
+          and 'channel_conversion' (if present).
+        ifabsent: string(volts)
+        range: text
+        required: true
+        equals_string: volts
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_times
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_channels
+        - array:
+            dimensions:
+            - alias: num_times
+            - alias: num_channels
+            - alias: num_samples
   SpikeEventSeries:
     name: SpikeEventSeries
     description: 'Stores snapshots/snippets of recorded spike events (i.e., threshold
@@ -92,24 +140,15 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       data:
         name: data
         description: Spike waveforms.
-        range: numeric
+        range: SpikeEventSeries__data
         required: true
-        multivalued: false
+        inlined: true
-        any_of:
-        - array:
-            dimensions:
-            - alias: num_events
-            - alias: num_samples
-        - array:
-            dimensions:
-            - alias: num_events
-            - alias: num_channels
-            - alias: num_samples
       timestamps:
         name: timestamps
         description: Timestamps for samples stored in data, in seconds, relative to
@@ -123,6 +162,60 @@ classes:
         required: true
         multivalued: false
     tree_root: true
+  SpikeEventSeries__data:
+    name: SpikeEventSeries__data
+    description: Spike waveforms.
+    attributes:
+      name:
+        name: name
+        ifabsent: string(data)
+        identifier: true
+        range: string
+        required: true
+        equals_string: data
+      conversion:
+        name: conversion
+        description: Scalar to multiply each element in data to convert it to the
+          specified 'unit'. If the data are stored in acquisition system units or
+          other units that require a conversion to be interpretable, multiply the
+          data by 'conversion' to convert the data to the specified 'unit'. e.g. if
+          the data acquisition system stores values in this object as signed 16-bit
+          integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V
+          to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion'
+          multiplier to get from raw data acquisition values to recorded volts is
+          2.5/32768/8000 = 9.5367e-9.
+        ifabsent: float(1.0)
+        range: float32
+        required: false
+      resolution:
+        name: resolution
+        description: Smallest meaningful difference between values in data, stored
+          in the specified by unit, e.g., the change in value of the least significant
+          bit, or a larger number if signal noise is known to be present. If unknown,
+          use -1.0.
+        ifabsent: float(-1.0)
+        range: float32
+        required: false
+      unit:
+        name: unit
+        description: Unit of measurement for waveforms, which is fixed to 'volts'.
+        ifabsent: string(volts)
+        range: text
+        required: true
+        equals_string: volts
+      value:
+        name: value
+        range: numeric
+        any_of:
+        - array:
+            dimensions:
+            - alias: num_events
+            - alias: num_samples
+        - array:
+            dimensions:
+            - alias: num_events
+            - alias: num_channels
+            - alias: num_samples
   FeatureExtraction:
     name: FeatureExtraction
     description: Features, such as PC1 and PC2, that are extracted from signals stored
@@ -132,6 +225,7 @@ classes:
       name:
         name: name
         ifabsent: string(FeatureExtraction)
+        identifier: true
         range: string
         required: true
       description:
@@ -177,7 +271,7 @@ classes:
           was generated from.
         range: DynamicTableRegion
         required: true
-        multivalued: false
+        inlined: true
     tree_root: true
   EventDetection:
     name: EventDetection
@@ -187,6 +281,7 @@ classes:
       name:
         name: name
         ifabsent: string(EventDetection)
+        identifier: true
         range: string
         required: true
       detection_method:
@@ -195,7 +290,6 @@ classes:
           or dV/dT threshold, as well as relevant values.
         range: text
         required: true
-        multivalued: false
       source_idx:
         name: source_idx
         description: Indices (zero-based) into source ElectricalSeries::data array
@@ -224,7 +318,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: ElectricalSeries
         - range: string
@@ -236,12 +330,19 @@ classes:
       during experiment acquisition.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(EventWaveform)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: SpikeEventSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: SpikeEventSeries
     tree_root: true
   FilteredEphys:
     name: FilteredEphys
@@ -258,12 +359,19 @@ classes:
       the ElectricalSeries.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(FilteredEphys)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: ElectricalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: ElectricalSeries
     tree_root: true
   LFP:
     name: LFP
@@ -272,12 +380,19 @@ classes:
       properties should be noted in the ElectricalSeries description or comments field.
     is_a: NWBDataInterface
     attributes:
-    - name: value
+      name:
-      multivalued: true
+        name: name
-      inlined: true
+        ifabsent: string(LFP)
-      inlined_as_list: false
+        identifier: true
-      any_of:
+        range: string
-      - range: ElectricalSeries
+        required: true
+      value:
+        name: value
+        multivalued: true
+        inlined: true
+        inlined_as_list: false
+        any_of:
+        - range: ElectricalSeries
     tree_root: true
   ElectrodeGroup:
     name: ElectrodeGroup
@@ -286,6 +401,7 @@ classes:
     attributes:
       name:
         name: name
+        identifier: true
         range: string
         required: true
       description:
@@ -304,8 +420,7 @@ classes:
         name: position
         description: stereotaxic or common framework coordinates
         range: ElectrodeGroup__position
-        required: false
+        inlined: true
-        multivalued: false
       device:
         name: device
         annotations:
@@ -313,7 +428,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Device
         - range: string
@@ -325,6 +440,7 @@ classes:
       name:
         name: name
         ifabsent: string(position)
+        identifier: true
         range: string
         required: true
         equals_string: position
@@ -334,24 +450,18 @@ classes:
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
       y:
         name: y
         description: y coordinate
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
       z:
         name: z
         description: z coordinate
         array:
           exact_number_dimensions: 1
         range: float32
-        required: false
-        multivalued: false
   ClusterWaveforms:
     name: ClusterWaveforms
     description: DEPRECATED The mean waveform shape, including standard deviation,
@@ -365,6 +475,7 @@ classes:
       name:
         name: name
         ifabsent: string(ClusterWaveforms)
+        identifier: true
         range: string
         required: true
       waveform_filtering:
@@ -372,7 +483,6 @@ classes:
         description: Filtering applied to data before generating mean/sd
         range: text
         required: true
-        multivalued: false
       waveform_mean:
         name: waveform_mean
         description: The mean waveform for each cluster, using the same indices for
@@ -404,7 +514,7 @@ classes:
             tag: source_type
             value: link
         required: true
-        multivalued: false
+        inlined: true
         any_of:
         - range: Clustering
         - range: string
@@ -418,6 +528,7 @@ classes:
       name:
         name: name
         ifabsent: string(Clustering)
+        identifier: true
         range: string
         required: true
       description:
@@ -426,7 +537,6 @@ classes:
           clusters curated using Klusters, etc)
         range: text
         required: true
-        multivalued: false
       num:
         name: num
         description: Cluster number of each event