diff --git a/SAS/TMSS/backend/src/tmss/tmssapp/populate.py b/SAS/TMSS/backend/src/tmss/tmssapp/populate.py
index b1a4694c8df1b913fb785d3c81c8177d2e471254..ecc12d4d65dc6c660b50a9f682b8572ab6ac1c56 100644
--- a/SAS/TMSS/backend/src/tmss/tmssapp/populate.py
+++ b/SAS/TMSS/backend/src/tmss/tmssapp/populate.py
@@ -240,46 +240,32 @@ def populate_connectors():
     # until the number of connectors throw too large. By then, we could consider introducing
     # wild cards, like output_of=NULL meaning "any".
 
-    # preprocessing pipeline input
-    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.INPUT.value),
-                                 datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='calibrator observation'),
-                                 input_of=TaskTemplate.objects.get(name='preprocessing pipeline'))
-
-    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.CORRELATOR.value),
-                                 datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='calibrator observation'),
-                                 input_of=TaskTemplate.objects.get(name='preprocessing pipeline'))
-
+    # calibrator observation
     TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.CORRELATOR.value),
                                  datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='target observation'),
-                                 input_of=TaskTemplate.objects.get(name='preprocessing pipeline'))
+                                 output_of=TaskTemplate.objects.get(name='calibrator observation'))
 
-    # ingest input
+    # target observation
     TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.CORRELATOR.value),
                                  datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='target observation'),
-                                 input_of=TaskTemplate.objects.get(name='ingest'))
+                                 output_of=TaskTemplate.objects.get(name='target observation'))
 
-    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.CORRELATOR.value),
+    # preprocessing pipeline
+    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.INPUT.value),
                                  datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='calibrator observation'),
-                                 input_of=TaskTemplate.objects.get(name='ingest'))
+                                 input_of=TaskTemplate.objects.get(name='preprocessing pipeline'))
 
-    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.CORRELATOR.value),
+    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.OUTPUT.value),
                                  datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='target observation'),
-                                 input_of=TaskTemplate.objects.get(name='ingest'))
+                                 input_of=TaskTemplate.objects.get(name='preprocessing pipeline'))
 
-    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.CORRELATOR.value),
+    # ingest
+    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.INPUT.value),
                                  datatype=Datatype.objects.get(value=Datatype.Choices.VISIBILITIES.value),
-                                 output_of=TaskTemplate.objects.get(name='preprocessing pipeline'),
                                  input_of=TaskTemplate.objects.get(name='ingest'))
 
-    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.BEAMFORMER.value),
+    TaskConnectorType.objects.create(role=Role.objects.get(value=Role.Choices.INPUT.value),
                                  datatype=Datatype.objects.get(value=Datatype.Choices.TIME_SERIES.value),
-                                 output_of=TaskTemplate.objects.get(name='beamforming observation'),
                                  input_of=TaskTemplate.objects.get(name='ingest'))