diff --git a/h5rdmtoolbox/wrapper/core.py b/h5rdmtoolbox/wrapper/core.py
index 437f5a90..80f0401d 100644
--- a/h5rdmtoolbox/wrapper/core.py
+++ b/h5rdmtoolbox/wrapper/core.py
@@ -1668,12 +1668,18 @@ def __setitem__(self, key, value):
             super().__setitem__(key, value)
 
     @dataset_value_decoder
-    def __getitem__(self, args, new_dtype=None, nparray=False) -> Union[xr.DataArray, np.ndarray]:
+    def __getitem__(self, args, new_dtype=None, nparray=False, links_as_strings:bool=False) -> Union[xr.DataArray, np.ndarray]:
         """Return sliced HDF dataset. If global setting `return_xarray`
         is set to True, a `xr.DataArray` is returned, otherwise the default
         behaviour of the h5p-package is used and a np.ndarray is returned.
         Note, that even if `return_xarray` is True, there is another way to
-        receive  numpy array. This is by calling .values[:] on the dataset."""
+        receive  numpy array. This is by calling .values[:] on the dataset.
+
+        Parameters
+        ----------
+        links_as_strings: bool
+            Attributes, that are links to other datasets or groups are returned as strings.
+        """
 
         args = args if isinstance(args, tuple) else (args,)
 
@@ -1691,7 +1697,16 @@ def __getitem__(self, args, new_dtype=None, nparray=False) -> Union[xr.DataArray
             args = tuple(args)
 
         arr = super().__getitem__(args, new_dtype=new_dtype)
-        ds_attrs = self.attrs
+
+        if links_as_strings:
+            attrs = dict(self.attrs)
+            for k, v in attrs.copy().items():
+                if isinstance(v, (h5py.Group, h5py.Dataset)):
+                    attrs[k] = v.name
+            ds_attrs = attrs
+        else:
+            ds_attrs = self.attrs
+
         attrs = pop_hdf_attributes(ds_attrs)
 
         if 'DIMENSION_LIST' in ds_attrs:
diff --git a/h5rdmtoolbox/wrapper/ds_decoder.py b/h5rdmtoolbox/wrapper/ds_decoder.py
index 5a1c149e..6cf1d374 100644
--- a/h5rdmtoolbox/wrapper/ds_decoder.py
+++ b/h5rdmtoolbox/wrapper/ds_decoder.py
@@ -68,6 +68,7 @@ def wrapper(*args, **kwargs):
         """wrapper that decodes the xarray.DataArray object"""
         ds = args[0]
         assert isinstance(ds, h5py.Dataset)
+        kwargs.update(links_as_strings=True)
         xarr = func(*args, **kwargs)
 
         parent_slice = args[1]
diff --git a/tests/wrapper/test_core.py b/tests/wrapper/test_core.py
index e03cc438..2ff7131d 100644
--- a/tests/wrapper/test_core.py
+++ b/tests/wrapper/test_core.py
@@ -1,12 +1,13 @@
 import datetime
-import h5py
 import json
-import numpy as np
-import pandas as pd
 import pathlib
 import unittest
-import xarray as xr
 from datetime import datetime, timedelta
+
+import h5py
+import numpy as np
+import pandas as pd
+import xarray as xr
 from numpy import linspace as ls
 
 import h5rdmtoolbox as h5tbx
@@ -28,7 +29,8 @@ def test_lower(self):
         self.assertEqual(h5tbx.Lower('Hello'), 'hello')
         self.assertIsInstance(h5tbx.lower('Hello'), h5tbx.Lower)
 
-    def tearDownClass():
+    @classmethod
+    def tearDownClass(cls) -> None:
         h5tbx.set_config(auto_create_h5tbx_version=False)
 
     def test_File(self):
@@ -771,3 +773,17 @@ def test_multidim_time_ds(self):
             self.assertIsInstance(t, xr.DataArray)
             self.assertEqual(t.shape, (2, 3))
             self.assertIsInstance(t[0, 0].values, np.datetime64)
+
+    def test_attr_group_link_and_xarray(self):
+        with h5tbx.File() as h5:
+            grp = h5.create_group('my_grp')
+            ds = h5.create_dataset(name='ds', data=4)
+
+            ds.attrs['link to grp'] = grp
+
+            self.assertIsInstance(ds.attrs['link to grp'], h5py.Group)
+
+            da = ds[()]
+            self.assertIsInstance(da, xr.DataArray)
+            self.assertIsInstance(da.attrs['link to grp'], str)
+            print(da)