diff --git a/holoviews/core/data/iris.py b/holoviews/core/data/iris.py
index 84e2ccffd4..c114d621a9 100644
--- a/holoviews/core/data/iris.py
+++ b/holoviews/core/data/iris.py
@@ -75,16 +75,18 @@ def init(cls, eltype, data, kdims, vdims):
             kdim_names = [kd.name for kd in eltype.kdims]
 
         if not isinstance(data, iris.cube.Cube):
+            ndims = len(kdim_names)
+            kdims = [kd if isinstance(kd, Dimension) else Dimension(kd)
+                     for kd in kdims]
+            vdim = vdims[0].name if isinstance(vdims[0], Dimension) else vdims[0]
             if isinstance(data, tuple):
-                coords = [iris.coords.DimCoord(vals, long_name=kd)
-                          for kd, vals in zip(kdim_names, data)]
                 value_array = data[-1]
-                vdim = vdims[0].name if isinstance(vdims[0], Dimension) else vdims[0]
+                data = {d: vals for d, vals in zip(kdim_names + [vdim], data)}
             elif isinstance(data, dict):
-                vdim = vdims[0].name if isinstance(vdims[0], Dimension) else vdims[0]
-                coords = [iris.coords.DimCoord(vals, long_name=kd)
-                          for kd, vals in data.items() if kd in kdims]
                 value_array = data[vdim]
+            coords = [(iris.coords.DimCoord(data[kd.name], long_name=kd.name,
+                                            units=kd.unit), ndims-n-1)
+                      for n, kd in enumerate(kdims)]
             try:
                 data = iris.cube.Cube(value_array, long_name=vdim,
                                       dim_coords_and_dims=coords)
@@ -222,6 +224,25 @@ def aggregate(cls, columns, kdims, function, **kwargs):
         raise NotImplementedError
 
 
+    @classmethod
+    def sample(cls, dataset, samples=[]):
+        """
+        Sampling currently not implemented.
+        """
+        raise NotImplementedError
+
+
+    @classmethod
+    def add_dimension(cls, columns, dimension, dim_pos, values, vdim):
+        """
+        Adding value dimensions not currently supported by iris interface.
+        Adding key dimensions not possible on dense interfaces.
+        """
+        if not vdim:
+            raise Exception("Cannot add key dimension to a dense representation.")
+        raise NotImplementedError
+
+
     @classmethod
     def select_to_constraint(cls, selection):
         """
@@ -232,7 +253,7 @@ def select_to_constraint(cls, selection):
             if isinstance(constraint, slice):
                 constraint = (constraint.start, constraint.stop)
             if isinstance(constraint, tuple):
-                constraint = iris.util.between(*constraint)
+                constraint = iris.util.between(*constraint, rh_inclusive=False)
             constraint_kwargs[dim] = constraint
         return iris.Constraint(**constraint_kwargs)
 
@@ -244,8 +265,9 @@ def select(cls, dataset, selection_mask=None, **selection):
         """
         constraint = cls.select_to_constraint(selection)
         pre_dim_coords = [c.name() for c in dataset.data.dim_coords]
+        indexed = cls.indexed(dataset, selection)
         extracted = dataset.data.extract(constraint)
-        if not extracted.dim_coords:
+        if indexed and not extracted.dim_coords:
             return extracted.data.item()
         post_dim_coords = [c.name() for c in extracted.dim_coords]
         dropped = [c for c in pre_dim_coords if c not in post_dim_coords]
diff --git a/tests/testdataset.py b/tests/testdataset.py
index 54c5aa305a..4b8e3b268e 100644
--- a/tests/testdataset.py
+++ b/tests/testdataset.py
@@ -404,7 +404,7 @@ def test_dataset_double_zip_init(self):
 
 class GridDatasetTest(HomogeneousColumnTypes, ComparisonTestCase):
     """
-    Test of the NdDataset interface (mostly for backwards compatibility)
+    Test of the Grid array interface
     """
 
     def setUp(self):
@@ -480,3 +480,36 @@ def test_dataset_sort_vdim_hm(self):
     def test_dataset_groupby(self):
         self.assertEqual(self.dataset_hm.groupby('x').keys(), list(self.xs))
 
+
+
+class IrisDatasetTest(GridDatasetTest):
+    """
+    Tests for Iris interface
+    """
+
+    def setUp(self):
+        import iris
+        self.restore_datatype = Dataset.datatype
+        Dataset.datatype = ['cube']
+        self.data_instance_type = iris.cube.Cube
+        self.init_data()
+
+    # Disabled tests for NotImplemented methods
+    def test_dataset_add_dimensions_values_hm(self):
+        pass
+
+    def test_dataset_sort_vdim_hm(self):
+        pass
+
+    def test_dataset_1D_reduce_hm(self):
+        pass
+
+    def test_dataset_2D_reduce_hm(self):
+        pass
+
+    def test_dataset_2D_aggregate_partial_hm(self):
+        pass
+
+    def test_dataset_sample_hm(self):
+        pass
+
diff --git a/tests/testirisinterface.py b/tests/testirisinterface.py
index 0e0b35e8c3..16315a6227 100644
--- a/tests/testirisinterface.py
+++ b/tests/testirisinterface.py
@@ -15,6 +15,7 @@ class TestCube(ComparisonTestCase):
 
     def setUp(self):
         self.cube = lat_lon_cube()
+        self.epsilon = 0.01
 
     def test_dim_to_coord(self):
         dim = coord_to_dimension(self.cube.coords()[0])
@@ -70,7 +71,7 @@ def test_select_index(self):
 
     def test_select_slice(self):
         cube = Dataset(self.cube)
-        self.assertEqual(cube.select(longitude=(0, 1)).data.data,
+        self.assertEqual(cube.select(longitude=(0, 1+self.epsilon)).data.data,
                          np.array([[1,  2], [5,  6], [9, 10]], dtype=np.int32))
 
     def test_select_set(self):
@@ -84,8 +85,8 @@ def test_select_multi_index(self):
 
     def test_select_multi_slice1(self):
         cube = Dataset(self.cube)
-        self.assertEqual(cube.select(longitude=(0, 1),
-                                     latitude=(0, 1)).data.data,
+        self.assertEqual(cube.select(longitude=(0, 1+self.epsilon),
+                                     latitude=(0, 1+self.epsilon)).data.data,
                          np.array([[5,  6], [9, 10]], dtype=np.int32))
 
     def test_select_multi_slice2(self):