diff --git a/nwb_linkml/src/nwb_linkml/maps/dtype.py b/nwb_linkml/src/nwb_linkml/maps/dtype.py
index 9419f01..64abf14 100644
--- a/nwb_linkml/src/nwb_linkml/maps/dtype.py
+++ b/nwb_linkml/src/nwb_linkml/maps/dtype.py
@@ -1,5 +1,6 @@
 import numpy as np
 from typing import Any
+from datetime import datetime
 
 flat_to_linkml = {
     "float" : "float",
@@ -67,6 +68,7 @@ np_to_python = {
     np.integer: int,
     np.byte: bytes,
     np.bytes_: bytes,
+    np.datetime64: datetime,
     **{n:int for n in (np.int8, np.int16, np.int32, np.int64, np.short, np.uint8, np.uint16, np.uint32, np.uint64, np.uint)},
     **{n:float for n in (np.float16, np.float32, np.floating, np.float32, np.float64, np.single, np.double, np.float_)},
     **{n:str for n in (np.character, np.str_, np.string_, np.unicode_)}
@@ -83,7 +85,8 @@ allowed_precisions = {
     'float16': ['float16', 'float32', 'float64'],
     'float32': ['float32', 'float64'],
     'utf': ['ascii'],
-    'number': ['short', 'int', 'long', 'int16', 'int32', 'int64', 'uint', 'uint8', 'uint16', 'uint32', 'uint64', 'float', 'float16', 'float32', 'float64']
+    'number': ['short', 'int', 'long', 'int16', 'int32', 'int64', 'uint', 'uint8', 'uint16', 'uint32', 'uint64', 'float', 'float16', 'float32', 'float64'],
+    'datetime64': ['object']
 }
 """
 Following HDMF, it turns out that specifying precision actually specifies minimum precision
diff --git a/nwb_linkml/src/nwb_linkml/maps/hdf5.py b/nwb_linkml/src/nwb_linkml/maps/hdf5.py
index 7c32a42..9392a95 100644
--- a/nwb_linkml/src/nwb_linkml/maps/hdf5.py
+++ b/nwb_linkml/src/nwb_linkml/maps/hdf5.py
@@ -9,6 +9,7 @@ import pdb
 from abc import abstractmethod
 from pathlib import Path
 from typing import Literal, List, Dict, Optional, Type, Union, Tuple
+import inspect
 
 import h5py
 from enum import StrEnum
@@ -20,6 +21,7 @@ from nwb_linkml.maps import Map
 from nwb_linkml.maps.hdmf import dynamictable_to_model
 from nwb_linkml.types.hdf5 import HDF5_Path
 from nwb_linkml.types.ndarray import NDArrayProxy
+from nwb_linkml.annotations import unwrap_optional
 
 
 class ReadPhases(StrEnum):
@@ -530,6 +532,16 @@ class CompleteModelGroups(HDF5Map):
         unpacked_results, errors, completes = resolve_references(src.result, completed)
         res.update(unpacked_results)
 
+        # now that we have the model in hand, we can solve any datasets that had an array
+        # but whose attributes are fixed (and thus should just be an array, rather than a subclass)
+        for k, v in src.model.model_fields.items():
+            annotation = unwrap_optional(v.annotation)
+            if inspect.isclass(annotation) and not issubclass(annotation, BaseModel):
+                if isinstance(res, dict) and k in res and isinstance(res[k], dict) and 'array' in res[k]:
+                    res[k] = res[k]['array']
+
+
+
         instance = src.model(**res)
         return H5ReadResult(
             path=src.path,
diff --git a/nwb_linkml/tests/test_io/test_io_hdf5.py b/nwb_linkml/tests/test_io/test_io_hdf5.py
index 47ac3b7..9d239d2 100644
--- a/nwb_linkml/tests/test_io/test_io_hdf5.py
+++ b/nwb_linkml/tests/test_io/test_io_hdf5.py
@@ -10,7 +10,6 @@ from ..fixtures import tmp_output_dir, set_config_vars, data_dir
 from nwb_linkml.io.hdf5 import HDF5IO
 from nwb_linkml.io.hdf5 import truncate_file
 
-@pytest.mark.skip()
 @pytest.mark.parametrize('dset', ['aibs.nwb'])
 def test_hdf_read(data_dir, dset):
     NWBFILE = data_dir / dset