diff --git a/processing/post/DADF5_vtk_cells.py b/processing/post/DADF5_vtk_cells.py
index 008ac5f66..85b999a19 100755
--- a/processing/post/DADF5_vtk_cells.py
+++ b/processing/post/DADF5_vtk_cells.py
@@ -5,6 +5,7 @@ import os,vtk
 import numpy as np
 import argparse
 import damask
+from vtk.util import numpy_support
 
 scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
@@ -36,7 +37,7 @@ for filename in options.filenames:
                   vtk.vtkDoubleArray(),
                  ]
 
-    rGrid.SetDimensions(*data.grid)
+    rGrid.SetDimensions(*(data.grid+1))
     for dim in [0,1,2]:
       for c in np.linspace(0,data.size[dim],1+data.grid[dim]):
         coordArray[dim].InsertNextValue(c)
@@ -47,8 +48,11 @@ for filename in options.filenames:
 
 
   for i,inc in enumerate(data.increments):
-    if not inc['active']: pass
-    
+    data.active['increments'] = [inc]
+    x = data.get_dataset_location('xi_sl')[0]
+    VTKarray = numpy_support.numpy_to_vtk(num_array=data.read_dataset(x,0),deep=True,array_type= vtk.VTK_DOUBLE)
+    VTKarray.SetName('xi_sl')
+    rGrid.GetCellData().AddArray(VTKarray)
     if data.structured:
       writer = vtk.vtkXMLRectilinearGridWriter()
 
diff --git a/python/damask/dadf5.py b/python/damask/dadf5.py
index 6342b18e7..043997547 100644
--- a/python/damask/dadf5.py
+++ b/python/damask/dadf5.py
@@ -1,6 +1,8 @@
 # -*- coding: UTF-8 no BOM -*-
 import h5py
 import re
+import numpy as np
+import os
 
 # ------------------------------------------------------------------
 class DADF5():
@@ -20,7 +22,7 @@ class DADF5():
     with h5py.File(filename,'r') as f:
       
       if f.attrs['DADF5-major'] != 0 or f.attrs['DADF5-minor'] != 1:
-        print('Unsupported DADF5 version {} '.format(f.attrs['DADF5-version']))
+        raise TypeError('Unsupported DADF5 version {} '.format(f.attrs['DADF5-version']))
     
       self.structured = 'grid' in f['mapping'].attrs.keys()
     
@@ -29,10 +31,49 @@ class DADF5():
         self.size = f['mapping'].attrs['size']
         
       r=re.compile('inc[0-9]+')
-      self.increments = [{'group':  u,
-                          'time':   f[u].attrs['time/s'],
-                          'active': True
+      self.increments = [{'inc':  int(u[3:]),
+                          'time': round(f[u].attrs['time/s'],12),
                           }   for u in f.keys() if r.match(u)]
+      
+      self.constituents   = np.unique(f['mapping/cellResults/constituent']['Name']).tolist()        # ToDo: I am not to happy with the name
+      self.constituents   = [c.decode() for c in self.constituents]
+      self.materialpoints = np.unique(f['mapping/cellResults/materialpoint']['Name']).tolist()      # ToDo: I am not to happy with the name
+      self.materialpoints = [m.decode() for m in self.materialpoints]
+      self.Nconstitutents = np.shape(f['mapping/cellResults/constituent'])[1]
+      self.Nmaterialpoints= np.shape(f['mapping/cellResults/constituent'])[0]
+      
+    self.active= {'increments'    :self.increments,
+                  'constituents'  :self.constituents,
+                  'materialpoints':self.materialpoints}
 
     self.filename   = filename
     self.mode       = mode
+
+
+  def get_dataset_location(self,label):
+    path = []
+    with h5py.File(self.filename,'r') as f:
+      for i in self.active['increments']:
+        group_inc = 'inc{:05}'.format(i['inc'])
+        for c in self.active['constituents']:
+          group_constituent = group_inc+'/constituent/'+c
+          for t in f[group_constituent].keys():
+            try:
+              f[group_constituent+'/'+t+'/'+label]
+              path.append(group_constituent+'/'+t+'/'+label)
+            except:
+              pass
+    return path
+    
+    
+  def read_dataset(self,path,c):
+    with h5py.File(self.filename,'r') as f:
+      shape = (self.Nmaterialpoints,) + np.shape(f[path])[1:]
+      dataset = np.full(shape,np.nan)
+      label   = path.split('/')[2]
+      p = np.where(f['mapping/cellResults/constituent'][:,c]['Name'] == str.encode(label))
+      for s in p: dataset[s,:] = f[path][s,:]
+    
+    return dataset
+        
+