diff --git a/src/lgdo/lh5/_serializers/read/array.py b/src/lgdo/lh5/_serializers/read/array.py
index 49f71600..138f0b49 100644
--- a/src/lgdo/lh5/_serializers/read/array.py
+++ b/src/lgdo/lh5/_serializers/read/array.py
@@ -9,26 +9,26 @@
 log = logging.getLogger(__name__)
 
 
-def _h5_read_array_generic(type_, name, h5f, **kwargs):
-    nda, attrs, n_rows_to_read = _h5_read_ndarray(name, h5f, **kwargs)
+def _h5_read_array_generic(type_, h5d, **kwargs):
+    nda, attrs, n_rows_to_read = _h5_read_ndarray(h5d, **kwargs)
 
     obj_buf = kwargs["obj_buf"]
 
     if obj_buf is None:
         return type_(nda=nda, attrs=attrs), n_rows_to_read
 
-    utils.check_obj_buf_attrs(obj_buf.attrs, attrs, h5f, name)
+    utils.check_obj_buf_attrs(obj_buf.attrs, attrs, h5d)
 
     return obj_buf, n_rows_to_read
 
 
-def _h5_read_array(name, h5f, **kwargs):
-    return _h5_read_array_generic(Array, name, h5f, **kwargs)
+def _h5_read_array(h5d, **kwargs):
+    return _h5_read_array_generic(Array, h5d, **kwargs)
 
 
-def _h5_read_fixedsize_array(name, h5f, **kwargs):
-    return _h5_read_array_generic(FixedSizeArray, name, h5f, **kwargs)
+def _h5_read_fixedsize_array(h5d, **kwargs):
+    return _h5_read_array_generic(FixedSizeArray, h5d, **kwargs)
 
 
-def _h5_read_array_of_equalsized_arrays(name, h5f, **kwargs):
-    return _h5_read_array_generic(ArrayOfEqualSizedArrays, name, h5f, **kwargs)
+def _h5_read_array_of_equalsized_arrays(h5d, **kwargs):
+    return _h5_read_array_generic(ArrayOfEqualSizedArrays, h5d, **kwargs)
diff --git a/src/lgdo/lh5/_serializers/read/composite.py b/src/lgdo/lh5/_serializers/read/composite.py
index f9a84b2c..6c0e9ba3 100644
--- a/src/lgdo/lh5/_serializers/read/composite.py
+++ b/src/lgdo/lh5/_serializers/read/composite.py
@@ -40,8 +40,7 @@
 
 
 def _h5_read_lgdo(
-    name,
-    h5f,
+    h5o,
     start_row=0,
     n_rows=sys.maxsize,
     idx=None,
@@ -52,11 +51,11 @@ def _h5_read_lgdo(
     decompress=True,
 ):
     # Handle list-of-files recursively
-    if not isinstance(h5f, (str, h5py.File)):
-        lh5_file = list(h5f)
+    if not isinstance(h5o, (h5py.Group, h5py.Dataset)):
+        lh5_objs = list(h5o)
         n_rows_read = 0
 
-        for i, _h5f in enumerate(lh5_file):
+        for i, _h5o in enumerate(lh5_objs):
             if isinstance(idx, list) and len(idx) > 0 and not np.isscalar(idx[0]):
                 # a list of lists: must be one per file
                 idx_i = idx[i]
@@ -65,7 +64,7 @@ def _h5_read_lgdo(
                 if not (isinstance(idx, tuple) and len(idx) == 1):
                     idx = (idx,)
                 # idx is a long continuous array
-                n_rows_i = read_n_rows(name, _h5f)
+                n_rows_i = read_n_rows(_h5o)
                 # find the length of the subset of idx that contains indices
                 # that are less than n_rows_i
                 n_rows_to_read_i = bisect.bisect_left(idx[0], n_rows_i)
@@ -77,8 +76,7 @@ def _h5_read_lgdo(
             n_rows_i = n_rows - n_rows_read
 
             obj_buf, n_rows_read_i = _h5_read_lgdo(
-                name,
-                _h5f,
+                _h5o,
                 start_row=start_row,
                 n_rows=n_rows_i,
                 idx=idx_i,
@@ -97,11 +95,8 @@ def _h5_read_lgdo(
 
         return obj_buf, n_rows_read
 
-    if not isinstance(h5f, h5py.File):
-        h5f = h5py.File(h5f, mode="r")
-
     log.debug(
-        f"reading {h5f.filename}:{name}[{start_row}:{n_rows}], decompress = {decompress}, "
+        f"reading {h5o.file.filename}:{h5o.name}[{start_row}:{n_rows}], decompress = {decompress}, "
         + (f" with field mask {field_mask}" if field_mask else "")
     )
 
@@ -110,15 +105,14 @@ def _h5_read_lgdo(
         idx = (idx,)
 
     try:
-        lgdotype = dtypeutils.datatype(h5f[name].attrs["datatype"])
+        lgdotype = dtypeutils.datatype(h5o.attrs["datatype"])
     except KeyError as e:
         msg = "dataset not in file or missing 'datatype' attribute"
-        raise LH5DecodeError(msg, h5f, name) from e
+        raise LH5DecodeError(msg, h5o) from e
 
     if lgdotype is Scalar:
         return _h5_read_scalar(
-            name,
-            h5f,
+            h5o,
             obj_buf=obj_buf,
         )
 
@@ -138,8 +132,7 @@ def _h5_read_lgdo(
 
     if lgdotype is Struct:
         return _h5_read_struct(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -164,8 +157,7 @@ def _h5_read_lgdo(
 
     if lgdotype is Table:
         return _h5_read_table(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -178,8 +170,7 @@ def _h5_read_lgdo(
 
     if lgdotype is ArrayOfEncodedEqualSizedArrays:
         return _h5_read_array_of_encoded_equalsized_arrays(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -191,8 +182,7 @@ def _h5_read_lgdo(
 
     if lgdotype is VectorOfEncodedVectors:
         return _h5_read_vector_of_encoded_vectors(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -204,8 +194,7 @@ def _h5_read_lgdo(
 
     if lgdotype is VectorOfVectors:
         return _h5_read_vector_of_vectors(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -216,8 +205,7 @@ def _h5_read_lgdo(
 
     if lgdotype is FixedSizeArray:
         return _h5_read_fixedsize_array(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -228,8 +216,7 @@ def _h5_read_lgdo(
 
     if lgdotype is ArrayOfEqualSizedArrays:
         return _h5_read_array_of_equalsized_arrays(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -240,8 +227,7 @@ def _h5_read_lgdo(
 
     if lgdotype is Array:
         return _h5_read_array(
-            name,
-            h5f,
+            h5o,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -251,12 +237,11 @@ def _h5_read_lgdo(
         )
 
     msg = f"no rule to decode {lgdotype.__name__} from LH5"
-    raise LH5DecodeError(msg, h5f, name)
+    raise LH5DecodeError(msg, h5o)
 
 
 def _h5_read_struct(
-    name,
-    h5f,
+    h5g,
     start_row=0,
     n_rows=sys.maxsize,
     idx=None,
@@ -269,7 +254,7 @@ def _h5_read_struct(
     # table... Maybe should emit a warning? Or allow them to be
     # dicts keyed by field name?
 
-    attrs = dict(h5f[name].attrs)
+    attrs = dict(h5g.attrs)
 
     # determine fields to be read out
     all_fields = dtypeutils.get_struct_fields(attrs["datatype"])
@@ -288,8 +273,7 @@ def _h5_read_struct(
         # support for integer keys
         field_key = int(field) if attrs.get("int_keys") else str(field)
         obj_dict[field_key], _ = _h5_read_lgdo(
-            f"{name}/{field}",
-            h5f,
+            h5g[field],
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -301,8 +285,7 @@ def _h5_read_struct(
 
 
 def _h5_read_table(
-    name,
-    h5f,
+    h5g,
     start_row=0,
     n_rows=sys.maxsize,
     idx=None,
@@ -314,9 +297,9 @@ def _h5_read_table(
 ):
     if obj_buf is not None and not isinstance(obj_buf, Table):
         msg = "provided object buffer is not a Table"
-        raise LH5DecodeError(msg, h5f, name)
+        raise LH5DecodeError(msg, h5g)
 
-    attrs = dict(h5f[name].attrs)
+    attrs = dict(h5g.attrs)
 
     # determine fields to be read out
     all_fields = dtypeutils.get_struct_fields(attrs["datatype"])
@@ -337,13 +320,12 @@ def _h5_read_table(
         if obj_buf is not None:
             if not isinstance(obj_buf, Table) or field not in obj_buf:
                 msg = "provided object buffer is not a Table or columns are missing"
-                raise LH5DecodeError(msg, h5f, name)
+                raise LH5DecodeError(msg, h5g)
 
             fld_buf = obj_buf[field]
 
         col_dict[field], n_rows_read = _h5_read_lgdo(
-            f"{name}/{field}",
-            h5f,
+            h5g[field],
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -363,12 +345,12 @@ def _h5_read_table(
         n_rows_read = rows_read[0]
     else:
         n_rows_read = 0
-        log.warning(f"Table '{name}' has no fields specified by {field_mask=}")
+        log.warning(f"Table '{h5g.name}' has no fields specified by {field_mask=}")
 
     for n in rows_read[1:]:
         if n != n_rows_read:
             log.warning(
-                f"Table '{name}' got strange n_rows_read = {n}, "
+                f"Table '{h5g.name}' got strange n_rows_read = {n}, "
                 "{n_rows_read} was expected ({rows_read})"
             )
 
@@ -400,6 +382,6 @@ def _h5_read_table(
     obj_buf.loc = obj_buf_start + n_rows_read
 
     # check attributes
-    utils.check_obj_buf_attrs(obj_buf.attrs, attrs, h5f, name)
+    utils.check_obj_buf_attrs(obj_buf.attrs, attrs, h5g)
 
     return obj_buf, n_rows_read
diff --git a/src/lgdo/lh5/_serializers/read/encoded.py b/src/lgdo/lh5/_serializers/read/encoded.py
index 0e63ebc8..23876c91 100644
--- a/src/lgdo/lh5/_serializers/read/encoded.py
+++ b/src/lgdo/lh5/_serializers/read/encoded.py
@@ -19,25 +19,22 @@
 
 
 def _h5_read_array_of_encoded_equalsized_arrays(
-    name,
-    h5f,
+    h5g,
     **kwargs,
 ):
-    return _h5_read_encoded_array(ArrayOfEncodedEqualSizedArrays, name, h5f, **kwargs)
+    return _h5_read_encoded_array(ArrayOfEncodedEqualSizedArrays, h5g, **kwargs)
 
 
 def _h5_read_vector_of_encoded_vectors(
-    name,
-    h5f,
+    h5g,
     **kwargs,
 ):
-    return _h5_read_encoded_array(VectorOfEncodedVectors, name, h5f, **kwargs)
+    return _h5_read_encoded_array(VectorOfEncodedVectors, h5g, **kwargs)
 
 
 def _h5_read_encoded_array(
     lgdotype,
-    name,
-    h5f,
+    h5g,
     start_row=0,
     n_rows=sys.maxsize,
     idx=None,
@@ -48,11 +45,11 @@ def _h5_read_encoded_array(
 ):
     if lgdotype not in (ArrayOfEncodedEqualSizedArrays, VectorOfEncodedVectors):
         msg = f"unsupported read of encoded type {lgdotype.__name__}"
-        raise LH5DecodeError(msg, h5f, name)
+        raise LH5DecodeError(msg, h5g)
 
     if not decompress and obj_buf is not None and not isinstance(obj_buf, lgdotype):
         msg = f"object buffer is not a {lgdotype.__name__}"
-        raise LH5DecodeError(msg, h5f, name)
+        raise LH5DecodeError(msg, h5g)
 
     # read out decoded_size, either a Scalar or an Array
     decoded_size_buf = encoded_data_buf = None
@@ -62,8 +59,7 @@ def _h5_read_encoded_array(
 
     if lgdotype is VectorOfEncodedVectors:
         decoded_size, _ = _h5_read_array(
-            f"{name}/decoded_size",
-            h5f,
+            h5g["decoded_size"],
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
@@ -74,15 +70,13 @@ def _h5_read_encoded_array(
 
     else:
         decoded_size, _ = _h5_read_scalar(
-            f"{name}/decoded_size",
-            h5f,
+            h5g["decoded_size"],
             obj_buf=None if decompress else decoded_size_buf,
         )
 
     # read out encoded_data, a VectorOfVectors
     encoded_data, n_rows_read = _h5_read_vector_of_vectors(
-        f"{name}/encoded_data",
-        h5f,
+        h5g["encoded_data"],
         start_row=start_row,
         n_rows=n_rows,
         idx=idx,
@@ -99,7 +93,7 @@ def _h5_read_encoded_array(
     rawdata = lgdotype(
         encoded_data=encoded_data,
         decoded_size=decoded_size,
-        attrs=h5f[name].attrs,
+        attrs=dict(h5g.attrs),
     )
 
     # already return if no decompression is requested
diff --git a/src/lgdo/lh5/_serializers/read/ndarray.py b/src/lgdo/lh5/_serializers/read/ndarray.py
index 46571a32..3d626f70 100644
--- a/src/lgdo/lh5/_serializers/read/ndarray.py
+++ b/src/lgdo/lh5/_serializers/read/ndarray.py
@@ -14,8 +14,7 @@
 
 
 def _h5_read_ndarray(
-    name,
-    h5f,
+    h5d,
     start_row=0,
     n_rows=sys.maxsize,
     idx=None,
@@ -25,16 +24,16 @@ def _h5_read_ndarray(
 ):
     if obj_buf is not None and not isinstance(obj_buf, Array):
         msg = "object buffer is not an Array"
-        raise LH5DecodeError(msg, h5f, name)
+        raise LH5DecodeError(msg, h5d)
 
     # compute the number of rows to read
     # we culled idx above for start_row and n_rows, now we have to apply
     # the constraint of the length of the dataset
     try:
-        ds_n_rows = h5f[name].shape[0]
+        ds_n_rows = h5d.shape[0]
     except AttributeError as e:
         msg = "does not seem to be an HDF5 dataset"
-        raise LH5DecodeError(msg, h5f, name) from e
+        raise LH5DecodeError(msg, h5d) from e
 
     if idx is not None:
         if len(idx[0]) > 0 and idx[0][-1] >= ds_n_rows:
@@ -78,23 +77,23 @@ def _h5_read_ndarray(
         # this is required to make the read of multiple files faster
         # until a better solution found.
         if change_idx_to_slice or idx is None or use_h5idx:
-            h5f[name].read_direct(obj_buf.nda, source_sel, dest_sel)
+            h5d.read_direct(obj_buf.nda, source_sel, dest_sel)
         else:
             # it is faster to read the whole object and then do fancy indexing
-            obj_buf.nda[dest_sel] = h5f[name][...][source_sel]
+            obj_buf.nda[dest_sel] = h5d[...][source_sel]
 
         nda = obj_buf.nda
     elif n_rows == 0:
-        tmp_shape = (0,) + h5f[name].shape[1:]
-        nda = np.empty(tmp_shape, h5f[name].dtype)
+        tmp_shape = (0,) + h5d.shape[1:]
+        nda = np.empty(tmp_shape, h5d.dtype)
     elif change_idx_to_slice or idx is None or use_h5idx:
-        nda = h5f[name][source_sel]
+        nda = h5d[source_sel]
     else:
         # it is faster to read the whole object and then do fancy indexing
-        nda = h5f[name][...][source_sel]
+        nda = h5d[...][source_sel]
 
     # Finally, set attributes and return objects
-    attrs = h5f[name].attrs
+    attrs = dict(h5d.attrs)
 
     # special handling for bools
     # (c and Julia store as uint8 so cast to bool)
diff --git a/src/lgdo/lh5/_serializers/read/scalar.py b/src/lgdo/lh5/_serializers/read/scalar.py
index 1eb02e43..db5ed5fe 100644
--- a/src/lgdo/lh5/_serializers/read/scalar.py
+++ b/src/lgdo/lh5/_serializers/read/scalar.py
@@ -11,24 +11,24 @@
 
 
 def _h5_read_scalar(
-    name,
-    h5f,
+    h5d,
     obj_buf=None,
 ):
-    value = h5f[name][()]
+    value = h5d[()]
+    attrs = dict(h5d.attrs)
 
     # special handling for bools
     # (c and Julia store as uint8 so cast to bool)
-    if h5f[name].attrs["datatype"] == "bool":
+    if attrs["datatype"] == "bool":
         value = np.bool_(value)
 
     if obj_buf is not None:
         if not isinstance(obj_buf, Scalar):
             msg = "object buffer a Scalar"
-            raise LH5DecodeError(msg, h5f, name)
+            raise LH5DecodeError(msg, h5d)
 
         obj_buf.value = value
-        obj_buf.attrs.update(h5f[name].attrs)
+        obj_buf.attrs.update(attrs)
         return obj_buf, 1
 
-    return Scalar(value=value, attrs=h5f[name].attrs), 1
+    return Scalar(value=value, attrs=attrs), 1
diff --git a/src/lgdo/lh5/_serializers/read/utils.py b/src/lgdo/lh5/_serializers/read/utils.py
index 923b2256..7f675fd7 100644
--- a/src/lgdo/lh5/_serializers/read/utils.py
+++ b/src/lgdo/lh5/_serializers/read/utils.py
@@ -3,10 +3,10 @@
 from ...exceptions import LH5DecodeError
 
 
-def check_obj_buf_attrs(attrs, new_attrs, file, name):
+def check_obj_buf_attrs(attrs, new_attrs, obj):
     if set(attrs.keys()) != set(new_attrs.keys()):
         msg = (
             f"existing buffer and new data chunk have different attributes: "
-            f"obj_buf.attrs={attrs} != {file.filename}[{name}].attrs={new_attrs}"
+            f"obj_buf.attrs={attrs} != {obj.file.filename}[{obj.name}].attrs={new_attrs}"
         )
-        raise LH5DecodeError(msg, file, name)
+        raise LH5DecodeError(msg, obj)
diff --git a/src/lgdo/lh5/_serializers/read/vector_of_vectors.py b/src/lgdo/lh5/_serializers/read/vector_of_vectors.py
index 1a699527..4c4c7655 100644
--- a/src/lgdo/lh5/_serializers/read/vector_of_vectors.py
+++ b/src/lgdo/lh5/_serializers/read/vector_of_vectors.py
@@ -20,8 +20,7 @@
 
 
 def _h5_read_vector_of_vectors(
-    name,
-    h5f,
+    h5g,
     start_row=0,
     n_rows=sys.maxsize,
     idx=None,
@@ -31,13 +30,12 @@ def _h5_read_vector_of_vectors(
 ):
     if obj_buf is not None and not isinstance(obj_buf, VectorOfVectors):
         msg = "object buffer is not a VectorOfVectors"
-        raise LH5DecodeError(msg, h5f, name)
+        raise LH5DecodeError(msg, h5g)
 
     # read out cumulative_length
     cumulen_buf = None if obj_buf is None else obj_buf.cumulative_length
     cumulative_length, n_rows_read = _h5_read_array(
-        f"{name}/cumulative_length",
-        h5f,
+        h5g["cumulative_length"],
         start_row=start_row,
         n_rows=n_rows,
         idx=idx,
@@ -63,8 +61,7 @@ def _h5_read_vector_of_vectors(
             fd_start = 0  # this variable avoids an ndarray append
 
         fd_starts, fds_n_rows_read = _h5_read_array(
-            f"{name}/cumulative_length",
-            h5f,
+            h5g["cumulative_length"],
             start_row=start_row,
             n_rows=n_rows,
             idx=idx2,
@@ -101,7 +98,7 @@ def _h5_read_vector_of_vectors(
             # need to read out the cumulen sample -before- the first sample
             # read above in order to get the starting row of the first
             # vector to read out in flattened_data
-            fd_start = h5f[f"{name}/cumulative_length"][start_row - 1]
+            fd_start = h5g["cumulative_length"][start_row - 1]
 
             # check limits for values that will be used subsequently
             if this_cumulen_nda[-1] < fd_start:
@@ -115,7 +112,7 @@ def _h5_read_vector_of_vectors(
                     f"cumulative_length non-increasing between entries "
                     f"{start_row} and {start_row+n_rows_read}"
                 )
-                raise LH5DecodeError(msg, h5f, name)
+                raise LH5DecodeError(msg, h5g)
 
         # determine the number of rows for the flattened_data readout
         fd_n_rows = this_cumulen_nda[-1] if n_rows_read > 0 else 0
@@ -147,18 +144,17 @@ def _h5_read_vector_of_vectors(
             fd_buf.resize(fdb_size)
 
     # now read
-    lgdotype = dtypeutils.datatype(h5f[f"{name}/flattened_data"].attrs["datatype"])
+    lgdotype = dtypeutils.datatype(h5g["flattened_data"].attrs["datatype"])
     if lgdotype is Array:
         _func = _h5_read_array
     elif lgdotype is VectorOfVectors:
         _func = _h5_read_vector_of_vectors
     else:
         msg = "type {lgdotype.__name__} is not supported"
-        raise LH5DecodeError(msg, h5f, f"{name}/flattened_data")
+        raise LH5DecodeError(msg, h5g, "flattened_data")
 
     flattened_data, _ = _func(
-        f"{name}/flattened_data",
-        h5f,
+        h5g["flattened_data"],
         start_row=fd_start,
         n_rows=fd_n_rows,
         idx=fd_idx,
@@ -180,7 +176,7 @@ def _h5_read_vector_of_vectors(
         VectorOfVectors(
             flattened_data=flattened_data,
             cumulative_length=cumulative_length,
-            attrs=h5f[name].attrs,
+            attrs=dict(h5g.attrs),
         ),
         n_rows_read,
     )
diff --git a/src/lgdo/lh5/core.py b/src/lgdo/lh5/core.py
index c8a2888d..a98081ca 100644
--- a/src/lgdo/lh5/core.py
+++ b/src/lgdo/lh5/core.py
@@ -107,9 +107,20 @@ def read(
         `n_rows_read` will be``1``. For tables it is redundant with
         ``table.loc``. If `obj_buf` is ``None``, only `object` is returned.
     """
+    if isinstance(lh5_file, h5py.File):
+        lh5_obj = lh5_file[name]
+    elif isinstance(lh5_file, str):
+        lh5_file = h5py.File(lh5_file, mode="r")
+        lh5_obj = lh5_file[name]
+    else:
+        lh5_obj = []
+        for h5f in lh5_file:
+            if isinstance(lh5_file, str):
+                h5f = h5py.File(h5f, mode="r")  # noqa: PLW2901
+            lh5_obj += h5f[name]
+
     obj, n_rows_read = _serializers._h5_read_lgdo(
-        name,
-        lh5_file,
+        lh5_obj,
         start_row=start_row,
         n_rows=n_rows,
         idx=idx,
diff --git a/src/lgdo/lh5/exceptions.py b/src/lgdo/lh5/exceptions.py
index ba64e213..fc290691 100644
--- a/src/lgdo/lh5/exceptions.py
+++ b/src/lgdo/lh5/exceptions.py
@@ -4,11 +4,11 @@
 
 
 class LH5DecodeError(Exception):
-    def __init__(self, message: str, file: str, obj: str) -> None:
+    def __init__(self, message: str, obj: h5py.Dataset | h5py.Group) -> None:
         super().__init__(message)
 
-        self.file = file.filename if isinstance(file, h5py.File) else file
-        self.obj = obj
+        self.file = obj.file.filename
+        self.obj = obj.name
 
     def __str__(self) -> str:
         return (
diff --git a/src/lgdo/lh5/store.py b/src/lgdo/lh5/store.py
index 2be17860..b4c2e873 100644
--- a/src/lgdo/lh5/store.py
+++ b/src/lgdo/lh5/store.py
@@ -144,13 +144,12 @@ def read(
         """
         # grab files from store
         if not isinstance(lh5_file, (str, h5py.File)):
-            lh5_file = [self.gimme_file(f, "r") for f in list(lh5_file)]
+            lh5_obj = [self.gimme_file(f, "r")[name] for f in list(lh5_file)]
         else:
-            lh5_file = self.gimme_file(lh5_file, "r")
+            lh5_obj = self.gimme_file(lh5_file, "r")[name]
 
         return _serializers._h5_read_lgdo(
-            name,
-            lh5_file,
+            lh5_obj,
             start_row=start_row,
             n_rows=n_rows,
             idx=idx,
diff --git a/src/lgdo/lh5/utils.py b/src/lgdo/lh5/utils.py
index cf1fed04..73c192e5 100644
--- a/src/lgdo/lh5/utils.py
+++ b/src/lgdo/lh5/utils.py
@@ -29,7 +29,7 @@ def get_buffer(
     Sets size to `size` if object has a size.
     """
     obj, n_rows = _serializers._h5_read_lgdo(
-        name, lh5_file, n_rows=0, field_mask=field_mask
+        lh5_file[name], n_rows=0, field_mask=field_mask
     )
 
     if hasattr(obj, "resize") and size is not None: