diff --git a/src/calng/JungfrauCorrection.py b/src/calng/JungfrauCorrection.py
index 8dc6210a8e4d0173510e05606b70b01e042f9fd5..58d481c9a4aa6d14758c3d21f319b2a27d893e80 100644
--- a/src/calng/JungfrauCorrection.py
+++ b/src/calng/JungfrauCorrection.py
@@ -3,7 +3,6 @@ import enum
 import cupy
 import numpy as np
 from karabo.bound import (
-    BOOL_ELEMENT,
     DOUBLE_ELEMENT,
     KARABO_CLASSINFO,
     OUTPUT_CHANNEL,
@@ -99,14 +98,10 @@ class JungfrauGpuRunner(base_gpu.BaseGpuRunner):
     def _get_gain_map_for_preview(self):
         return self.input_gain_map_gpu
 
-    def load_data(self, image_data, input_gain_map, cell_table, daq_transpose=False):
+    def load_data(self, image_data, input_gain_map, cell_table):
         """Experiment: loading all three in one function as they are tied"""
-        if daq_transpose:
-            self.input_data_gpu[:] = cupy.asarray(image_data).transpose()[0]
-            self.input_gain_map_gpu[:] = cupy.asarray(input_gain_map).transpose()[0]
-        else:
-            self.input_data_gpu.set(image_data)
-            self.input_gain_map_gpu.set(input_gain_map)
+        self.input_data_gpu.set(image_data)
+        self.input_gain_map_gpu.set(input_gain_map)
         if self.burst_mode:
             self.cell_table_gpu.set(cell_table)
 
@@ -258,7 +253,6 @@ class JungfrauCorrection(BaseCorrection):
     _calcat_friend_class = JungfrauCalcatFriend
     _constant_enum_class = JungfrauConstants
     _managed_keys = BaseCorrection._managed_keys.copy()
-    _schema_cache_fields = BaseCorrection._schema_cache_fields.copy()
     _image_data_path = "data.adc"
     _cell_table_path = "data.memoryCell"
 
@@ -287,22 +281,6 @@ class JungfrauCorrection(BaseCorrection):
             .commit(),
         )
 
-        (
-            BOOL_ELEMENT(expected)
-            .key("dataFormat.daqTranspose")
-            .displayedName("Transpose axes from DAQ")
-            .description(
-                "Data on daqOutput channel has interesting axis order. In online "
-                "deployments, this means that a transpose is needed before correction."
-            )
-            .assignmentOptional()
-            .defaultValue(True)
-            .reconfigurable()
-            .commit(),
-        )
-        JungfrauCorrection._schema_cache_fields.add("dataFormat.daqTranspose")
-        JungfrauCorrection._managed_keys.add("dataFormat.daqTranspose")
-
         (
             OUTPUT_CHANNEL(expected)
             .key("preview.outputGainMap")
@@ -363,10 +341,7 @@ class JungfrauCorrection(BaseCorrection):
             cell_table = cell_table[np.newaxis]
         try:
             self.kernel_runner.load_data(
-                image_data,
-                data_hash.get("data.gain"),
-                cell_table,
-                daq_transpose=self._schema_cache["dataFormat.daqTranspose"]
+                image_data, data_hash.get("data.gain"), cell_table
             )
         except ValueError as e:
             self.log_status_warn(f"Failed to load data: {e}")