diff --git a/video_prediction_savp/HPC_scripts/data_extraction_era5_template.sh b/video_prediction_savp/HPC_scripts/data_extraction_era5_template.sh
index a80a3b8779908fc51121c6682817f20ec197a327..68e1c97c2575e6002694ca895f618a424f22d822 100644
--- a/video_prediction_savp/HPC_scripts/data_extraction_era5_template.sh
+++ b/video_prediction_savp/HPC_scripts/data_extraction_era5_template.sh
@@ -5,9 +5,9 @@
 #SBATCH --ntasks=13
 ##SBATCH --ntasks-per-node=13
 #SBATCH --cpus-per-task=1
-#SBATCH --output=DataExtraction-out.%j
-#SBATCH --error=DataExtraction-err.%j
-#SBATCH --time=05:00:00
+#SBATCH --output=data_extraction_era5-out.%j
+#SBATCH --error=data_extraction_era5-err.%j
+#SBATCH --time=00:20:00
 #SBATCH --partition=devel
 #SBATCH --mail-type=ALL
 #SBATCH --mail-user=b.gong@fz-juelich.de
diff --git a/video_prediction_savp/env_setup/create_env.sh b/video_prediction_savp/env_setup/create_env.sh
index 9f8a4c5aa007695a6d668040aacf08e158b3a12f..d014f5d37bd9f8f8eb900ff1529d98445b69f53d 100755
--- a/video_prediction_savp/env_setup/create_env.sh
+++ b/video_prediction_savp/env_setup/create_env.sh
@@ -32,7 +32,7 @@ fi
 
 # list of (Batch) scripts used for the steps in the workflow
 # !!! Expects that a template named [script_name]_template.sh exists!!!
-workflow_scripts=(DataExtraction DataPreprocess DataPreprocess2tf train_era5 generate_era5 DatePreprocess2tf_movingmnist train_movingmnist generate_movingmnist)
+workflow_scripts=(data_extraction_era5 preprocess_data_era5_step1 preprocess_data_era5_step2 train_model_era5 visualize_postprocess_era5 preprocess_data_moving_mnist train_model_moving_mnist visualize_postprocess_moving_mnist)
 
 HOST_NAME=`hostname`
 ENV_NAME=$1
diff --git a/video_prediction_savp/video_prediction/datasets/prepare_era5_data.py b/video_prediction_savp/utils/prepare_era5_data.py
similarity index 100%
rename from video_prediction_savp/video_prediction/datasets/prepare_era5_data.py
rename to video_prediction_savp/utils/prepare_era5_data.py
diff --git a/video_prediction_savp/video_prediction/datasets/process_netCDF_v2.py b/video_prediction_savp/utils/process_netCDF_v2.py
similarity index 100%
rename from video_prediction_savp/video_prediction/datasets/process_netCDF_v2.py
rename to video_prediction_savp/utils/process_netCDF_v2.py
diff --git a/video_prediction_savp/video_prediction/datasets/__init__.py b/video_prediction_savp/video_prediction/datasets/__init__.py
index f58607c2f4c14047aefb36956e98bd228a30aeb1..2cdad80fc658f4c1e4aa4725ac0d2da0cb9a65bd 100644
--- a/video_prediction_savp/video_prediction/datasets/__init__.py
+++ b/video_prediction_savp/video_prediction/datasets/__init__.py
@@ -6,7 +6,7 @@ from .softmotion_dataset import SoftmotionVideoDataset
 from .kth_dataset import KTHVideoDataset
 from .ucf101_dataset import UCF101VideoDataset
 from .cartgripper_dataset import CartgripperVideoDataset
-from .era5_dataset_v2 import ERA5Dataset_v2
+from .era5_dataset import ERA5Dataset
 from .moving_mnist import MovingMnist
 #from .era5_dataset_v2_anomaly import ERA5Dataset_v2_anomaly
 
diff --git a/video_prediction_savp/video_prediction/datasets/era5_dataset.py b/video_prediction_savp/video_prediction/datasets/era5_dataset.py
index 8835363a002c06f7e5cfcf337e4db07d280a3bc6..4d80aacf701f74aa03a948765086905b386c6bb5 100644
--- a/video_prediction_savp/video_prediction/datasets/era5_dataset.py
+++ b/video_prediction_savp/video_prediction/datasets/era5_dataset.py
@@ -12,8 +12,7 @@ from video_prediction.datasets.base_dataset import VarLenFeatureVideoDataset
 # ML 2020/04/14: hack for getting functions of process_netCDF_v2:
 from os import path
 import sys
-sys.path.append(path.abspath('../../workflow_parallel_frame_prediction/'))
-import DataPreprocess.process_netCDF_v2
+import video_prediction.datasets.process_netCDF_v2
 from general_utils import get_unique_vars
 from statistics import Calc_data_stat
 from metadata import MetaData
@@ -26,9 +25,9 @@ import glob
 
 
 
-class ERA5Dataset_v2(VarLenFeatureVideoDataset):
+class ERA5Dataset(VarLenFeatureVideoDataset):
     def __init__(self, *args, **kwargs):
-        super(ERA5Dataset_v2, self).__init__(*args, **kwargs)
+        super(ERA5Dataset, self).__init__(*args, **kwargs)
         from google.protobuf.json_format import MessageToDict
         example = next(tf.python_io.tf_record_iterator(self.filenames[0]))
         dict_message = MessageToDict(tf.train.Example.FromString(example))
@@ -39,7 +38,7 @@ class ERA5Dataset_v2(VarLenFeatureVideoDataset):
         self.state_like_names_and_shapes['images'] = 'images/encoded', self.image_shape
 
     def get_default_hparams_dict(self):
-        default_hparams = super(ERA5Dataset_v2, self).get_default_hparams_dict()
+        default_hparams = super(ERA5Dataset, self).get_default_hparams_dict()
         hparams = dict(
             context_frames=10,#Bing: Todo oriignal is 10
             sequence_length=20,#bing: TODO original is 20,
@@ -122,6 +121,9 @@ class ERA5Dataset_v2(VarLenFeatureVideoDataset):
         #    _parser, batch_size, drop_remainder=True, num_parallel_calls=num_parallel_calls)) #  Bing: Parallel data mapping, num_parallel_calls normally depends on the hardware, however, normally should be equal to be the usalbe number of CPUs
         dataset = dataset.prefetch(batch_size)  # Bing: Take the data to buffer inorder to save the waiting time for GPU
         return dataset
+/V2
+
+