diff --git a/aiida/orm/nodes/data/array/array.py b/aiida/orm/nodes/data/array/array.py
index 06e43a9f43..1bb97e94b3 100644
--- a/aiida/orm/nodes/data/array/array.py
+++ b/aiida/orm/nodes/data/array/array.py
@@ -193,3 +193,32 @@ def _validate(self):
                 f'Mismatch of files and properties for ArrayData node (pk= {self.pk}): {files} vs. {properties}'
             )
         super()._validate()
+
+    def _get_array_entries(self):
+        """Return a dictionary with the different array entries.
+
+        The idea is that this dictionary contains the array name as a key and
+        the value is the numpy array transformed into a list. This is so that
+        it can be transformed into a json object.
+        """
+        array_dict = {}
+        for key, val in self.get_iterarrays():
+            array_dict[key] = val.tolist()
+        return array_dict
+
+    def _prepare_json(self, main_file_name='', comments=True):  # pylint: disable=unused-argument
+        """Dump the content of the arrays stored in this node into JSON format.
+
+        :param comments: if True, includes comments (if it makes sense for the given format)
+        """
+        import json
+
+        from aiida import get_file_header
+
+        json_dict = self._get_array_entries()
+        json_dict['original_uuid'] = self.uuid
+
+        if comments:
+            json_dict['comments'] = get_file_header(comment_char='')
+
+        return json.dumps(json_dict).encode('utf-8'), {}
diff --git a/tests/orm/nodes/data/test_data.py b/tests/orm/nodes/data/test_data.py
index 5293ff6444..575ceca35d 100644
--- a/tests/orm/nodes/data/test_data.py
+++ b/tests/orm/nodes/data/test_data.py
@@ -21,6 +21,7 @@
 @pytest.fixture
 @pytest.mark.usefixtures('aiida_profile_clean')
 def generate_class_instance():
+    # pylint: disable=too-many-return-statements, too-many-statements
     """Generate a dummy `Data` instance for the given sub class."""
 
     def _generate_class_instance(data_class):
@@ -61,6 +62,57 @@ def _generate_class_instance(data_class):
             instance = data_class(file=filepath_carbon)
             return instance
 
+        if data_class is orm.ArrayData:
+            instance = data_class()
+            array_data = numpy.identity(3)
+            instance.set_array('data', array_data)
+            instance.set_array('contains_nan_inf', numpy.array([float('NaN'), float('Inf')]))
+            return instance
+
+        if data_class is orm.KpointsData:
+            instance = data_class()
+            cell = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
+            instance.set_cell(cell)
+            instance.set_kpoints_mesh_from_density(0.5)
+            return instance
+
+        if data_class is orm.XyData:
+            instance = data_class()
+            instance.set_x(numpy.arange(5), 'xdata', 'm')
+            instance.set_y(numpy.arange(5), 'ydata', 'm')
+            return instance
+
+        if data_class is orm.ProjectionData:
+
+            my_real_hydrogen_dict = {
+                'angular_momentum': -3,
+                'diffusivity': None,
+                'kind_name': 'As',
+                'magnetic_number': 0,
+                'position': [-1.420047044832945, 1.420047044832945, 1.420047044832945],
+                'radial_nodes': 0,
+                'spin': 0,
+                'spin_orientation': None,
+                'x_orientation': None,
+                'z_orientation': None
+            }
+            kpoints = orm.KpointsData()
+            kpoints.set_cell([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+            kpoints.set_kpoints([[0., 0., 0.]])
+            bands = orm.BandsData()
+            bands.set_kpointsdata(kpoints)
+            bands.set_bands([[1.0]])
+
+            RealHydrogen = plugins.OrbitalFactory('core.realhydrogen')  # pylint: disable=invalid-name
+            orbital = RealHydrogen(**my_real_hydrogen_dict)
+
+            instance = data_class()
+            instance.set_reference_bandsdata(bands)
+            instance.set_projectiondata(
+                orbital, list_of_pdos=numpy.asarray([1.0]), list_of_energy=numpy.asarray([1.0]), bands_check=False
+            )
+            return instance
+
         raise RuntimeError(
             'no instance generator implemented for class `{}`. If you have added a `_prepare_*` method '
             'for this data class, add a generator of a dummy instance here'.format(data_class)