diff --git a/hyppopy/solver.py b/hyppopy/solver.py
index 35de7c8..78d3917 100644
--- a/hyppopy/solver.py
+++ b/hyppopy/solver.py
@@ -1,86 +1,84 @@
-# -*- coding: utf-8 -*-
-#
 # DKFZ
 #
 #
 # Copyright (c) German Cancer Research Center,
 # Division of Medical and Biological Informatics.
 # All rights reserved.
 #
 # This software is distributed WITHOUT ANY WARRANTY; without
 # even the implied warranty of MERCHANTABILITY or FITNESS FOR
 # A PARTICULAR PURPOSE.
 #
 # See LICENSE.txt or http://www.mitk.org for details.
 #
 # Author: Sven Wanner (s.wanner@dkfz.de)
 
 import os
 import logging
 from hyppopy.globals import DEBUGLEVEL
 LOG = logging.getLogger(os.path.basename(__file__))
 LOG.setLevel(DEBUGLEVEL)
 
 
 class Solver(object):
     _name = None
     _solver_plugin = None
     _settings_plugin = None
 
     def __init__(self):
         pass
 
     def set_data(self, data):
         self.solver.set_data(data)
 
     def set_parameters(self, params):
         self.settings.set(params)
         self.settings.set_attributes(self.solver)
         self.settings.set_attributes(self.settings)
 
     def read_parameter(self, fname):
         self.settings.read(fname)
         self.settings.set_attributes(self.solver)
         self.settings.set_attributes(self.settings)
 
     def set_loss_function(self, loss_func):
         self.solver.set_loss_function(loss_func)
 
     def run(self):
         self.solver.settings = self.settings
         self.solver.run()
 
     def get_results(self):
         return self.solver.get_results()
 
     @property
     def is_ready(self):
         return self.solver is not None and self.settings is not None
 
     @property
     def solver(self):
         return self._solver_plugin
 
     @solver.setter
     def solver(self, value):
         self._solver_plugin = value
 
     @property
     def settings(self):
         return self._settings_plugin
 
     @settings.setter
     def settings(self, value):
         self._settings_plugin = value
 
     @property
     def name(self):
         return self._name
 
     @name.setter
     def name(self, value):
         if not isinstance(value, str):
             LOG.error(f"Invalid input, str type expected for value, got {type(value)} instead")
             raise IOError(f"Invalid input, str type expected for value, got {type(value)} instead")
         self._name = value
 
diff --git a/hyppopy/workflows/datalaoder/__init__.py b/hyppopy/workflows/datalaoder/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/hyppopy/workflows/datalaoder/dataloader.py b/hyppopy/workflows/datalaoder/dataloader.py
new file mode 100644
index 0000000..3d86ac4
--- /dev/null
+++ b/hyppopy/workflows/datalaoder/dataloader.py
@@ -0,0 +1,34 @@
+# DKFZ
+#
+#
+# Copyright (c) German Cancer Research Center,
+# Division of Medical and Biological Informatics.
+# All rights reserved.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without
+# even the implied warranty of MERCHANTABILITY or FITNESS FOR
+# A PARTICULAR PURPOSE.
+#
+# See LICENSE.txt or http://www.mitk.org for details.
+#
+# Author: Sven Wanner (s.wanner@dkfz.de)
+
+import abc
+
+
+class DataLoader(object):
+
+    def __init__(self):
+        self.data = None
+
+    @abc.abstractmethod
+    def read(self, **kwargs):
+        raise NotImplementedError("the read method has to be implemented in classes derived from DataLoader")
+
+    @abc.abstractmethod
+    def preprocess(self):
+        pass
+
+    def get(self):
+        self.preprocess()
+        return self.data
diff --git a/hyppopy/workflows/datalaoder/simpleloader.py b/hyppopy/workflows/datalaoder/simpleloader.py
new file mode 100644
index 0000000..4a8c461
--- /dev/null
+++ b/hyppopy/workflows/datalaoder/simpleloader.py
@@ -0,0 +1,41 @@
+# DKFZ
+#
+#
+# Copyright (c) German Cancer Research Center,
+# Division of Medical and Biological Informatics.
+# All rights reserved.
+#
+# This software is distributed WITHOUT ANY WARRANTY; without
+# even the implied warranty of MERCHANTABILITY or FITNESS FOR
+# A PARTICULAR PURPOSE.
+#
+# See LICENSE.txt or http://www.mitk.org for details.
+#
+# Author: Sven Wanner (s.wanner@dkfz.de)
+
+import os
+import numpy as np
+import pandas as pd
+
+from hyppopy.workflows.datalaoder.dataloader import DataLoader
+
+
+class SimpleDataLoader(DataLoader):
+
+    def read(self, **kwargs):
+        if kwargs['data_name'].endswith(".npy"):
+            if not kwargs['labels_name'].endswith(".npy"):
+                raise IOError("Expect both data_name and labels_name being of type .npy!")
+            self.data = [np.load(os.path.join(kwargs['path'], kwargs['data_name'])), np.load(os.path.join(kwargs['path'], kwargs['labels_name']))]
+        elif kwargs['data_name'].endswith(".csv"):
+            try:
+                dataset = pd.read_csv(os.path.join(kwargs['path'], kwargs['data_name']))
+                y = dataset[kwargs['labels_name']].values
+                X = dataset.drop([kwargs['labels_name']], axis=1).values
+                self.data = [X, y]
+            except Exception as e:
+                print("Precondition violation, this usage case expects as data_name a "
+                      "csv file and as label_name a name of a column in this csv table!")
+        else:
+            raise NotImplementedError("This combination of data_name and labels_name "
+                                      "does not yet exist, feel free to add it")
diff --git a/hyppopy/workflows/randomforest_usecase/randomforest_usecase.py b/hyppopy/workflows/randomforest_usecase/randomforest_usecase.py
index 18137ca..c7ca0bc 100644
--- a/hyppopy/workflows/randomforest_usecase/randomforest_usecase.py
+++ b/hyppopy/workflows/randomforest_usecase/randomforest_usecase.py
@@ -1,60 +1,38 @@
-# -*- coding: utf-8 -*-
-#
 # DKFZ
 #
 #
 # Copyright (c) German Cancer Research Center,
 # Division of Medical and Biological Informatics.
 # All rights reserved.
 #
 # This software is distributed WITHOUT ANY WARRANTY; without
 # even the implied warranty of MERCHANTABILITY or FITNESS FOR
 # A PARTICULAR PURPOSE.
 #
 # See LICENSE.txt or http://www.mitk.org for details.
 #
 # Author: Sven Wanner (s.wanner@dkfz.de)
 
-import os
-import numpy as np
-import pandas as pd
+
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.model_selection import cross_val_score
 
-from hyppopy.workflowbase import Workflow
-
-
-def data_loader(path, data_name, labels_name):
-    if data_name.endswith(".npy"):
-        if not labels_name.endswith(".npy"):
-            raise IOError("Expect both data_name and labels_name being of type .npy!")
-        data = [np.load(os.path.join(path, data_name)), np.load(os.path.join(path, labels_name))]
-    elif data_name.endswith(".csv"):
-        try:
-            dataset = pd.read_csv(os.path.join(path, data_name))
-            y = dataset[labels_name].values
-            X = dataset.drop([labels_name], axis=1).values
-            data = [X, y]
-        except Exception as e:
-            print("Precondition violation, this usage case expects as data_name a "
-                  "csv file and as label_name a name of a column in this csv table!")
-    else:
-        raise NotImplementedError("This combination of data_name and labels_name "
-                                  "does not yet exist, feel free to add it")
-    return data
+from hyppopy.workflows.workflowbase import Workflow
+from hyppopy.workflows.datalaoder.simpleloader import SimpleDataLoader
 
 
 class randomforest_usecase(Workflow):
 
     def __init__(self, args):
         Workflow.__init__(self, args)
 
     def setup(self):
-        data = data_loader(self.args.data, self.solver.settings.data_name, self.solver.settings.labels_name)
-        self.solver.set_data(data)
+        dl = SimpleDataLoader()
+        dl.read(path=self.args.data, data_name=self.solver.settings.data_name, labels_name=self.solver.settings.labels_name)
+        self.solver.set_data(dl.get())
 
     def blackbox_function(self, data, params):
         if "n_estimators" in params.keys():
             params["n_estimators"] = int(round(params["n_estimators"]))
         clf = RandomForestClassifier(**params)
         return -cross_val_score(estimator=clf, X=data[0], y=data[1], cv=3).mean()
diff --git a/hyppopy/workflows/svc_usecase/svc_usecase.py b/hyppopy/workflows/svc_usecase/svc_usecase.py
index 60ae83d..18f93f1 100644
--- a/hyppopy/workflows/svc_usecase/svc_usecase.py
+++ b/hyppopy/workflows/svc_usecase/svc_usecase.py
@@ -1,58 +1,41 @@
 # -*- coding: utf-8 -*-
 #
 # DKFZ
 #
 #
 # Copyright (c) German Cancer Research Center,
 # Division of Medical and Biological Informatics.
 # All rights reserved.
 #
 # This software is distributed WITHOUT ANY WARRANTY; without
 # even the implied warranty of MERCHANTABILITY or FITNESS FOR
 # A PARTICULAR PURPOSE.
 #
 # See LICENSE.txt or http://www.mitk.org for details.
 #
 # Author: Sven Wanner (s.wanner@dkfz.de)
 
 import os
 import numpy as np
 import pandas as pd
 from sklearn.svm import SVC
 from sklearn.model_selection import cross_val_score
 
-from hyppopy.workflowbase import Workflow
-
-
-def data_loader(path, data_name, labels_name):
-    if data_name.endswith(".npy"):
-        if not labels_name.endswith(".npy"):
-            raise IOError("Expect both data_name and labels_name being of type .npy!")
-        data = [np.load(os.path.join(path, data_name)), np.load(os.path.join(path, labels_name))]
-    elif data_name.endswith(".csv"):
-        try:
-            dataset = pd.read_csv(os.path.join(path, data_name))
-            y = dataset[labels_name].values
-            X = dataset.drop([labels_name], axis=1).values
-            data = [X, y]
-        except Exception as e:
-            print("Precondition violation, this usage case expects as data_name a "
-                  "csv file and as label_name a name of a column in this csv table!")
-    else:
-        raise NotImplementedError("This combination of data_name and labels_name "
-                                  "does not yet exist, feel free to add it")
-    return data
+from hyppopy.workflows.workflowbase import Workflow
+from hyppopy.workflows.datalaoder.simpleloader import SimpleDataLoader
 
 
 class svc_usecase(Workflow):
 
     def __init__(self, args):
         Workflow.__init__(self, args)
 
     def setup(self):
-        data = data_loader(self.args.data, self.solver.settings.data_name, self.solver.settings.labels_name)
-        self.solver.set_data(data)
+        dl = SimpleDataLoader()
+        dl.read(path=self.args.data, data_name=self.solver.settings.data_name,
+                labels_name=self.solver.settings.labels_name)
+        self.solver.set_data(dl.get())
 
     def blackbox_function(self, data, params):
         clf = SVC(**params)
         return -cross_val_score(estimator=clf, X=data[0], y=data[1], cv=3).mean()
diff --git a/hyppopy/workflowbase.py b/hyppopy/workflows/workflowbase.py
similarity index 100%
rename from hyppopy/workflowbase.py
rename to hyppopy/workflows/workflowbase.py