diff --git a/workflows/my-workflow.yaml b/workflows/my-workflow.yaml
new file mode 100644
index 0000000..8eac388
--- /dev/null
+++ b/workflows/my-workflow.yaml
@@ -0,0 +1,37 @@
+# === Welcome to the template Renku Workflow file! ===
+# You can use this file to encode in what order your data processing steps should be run,
+# making it easier for you to run your workflow, and for others to understand it!
+
+# === How to use this template ===
+# Replace the script and data paths in the template below to match your analysis commands. 
+# Then, run `renku run my-workflow.yaml` in a terminal to execute the workflow!
+# If you are working in a notebook, run `! renku run my-workflow.yaml` in a notebook cell. 
+
+# === Docs ===
+# To learn much more about what you can do with the Renku Workflow File, see our docs:
+# https://renku.readthedocs.io/en/stable/topic-guides/workflows/workflow-file.html
+
+name: my-workflow
+steps:
+  step-one:
+    command: python $n $my-script $input-data $output-data
+    inputs:
+      - my-script:
+          path: src/script.py
+      - input-data:
+          path: data/input/sample_data.csv
+    outputs:
+      - output-data:
+          path: data/output/results.csv
+    parameters:
+      - n:
+          prefix: -n
+          value: 10
+
+  # === Adding more steps ===
+  # You can add as many steps as you want to your workflow by copy and pasting the step template above
+  # TIP: To run just one step from a workflow, simply add the step name to the command, like this:
+  #   `renku run my-workflow.yaml make-plot`
+  # make-plot:
+    # command: python $another-script $output-data $my-plot
+    # ...
diff --git a/workflows/utils.py b/workflows/utils.py
new file mode 100644
index 0000000..9d4ff5d
--- /dev/null
+++ b/workflows/utils.py
@@ -0,0 +1,107 @@
+import yaml
+import os
+from collections import OrderedDict
+
+def generate_command(base_command='python', inputs=None, outputs=None, parameters=None):
+    inputs = inputs or []
+    outputs = outputs or []
+    placeholders = [
+        f"${name}"
+        for name, value in inputs + parameters + outputs
+        if isinstance(value, dict) and not value.get('implicit', False)
+    ]
+    return f"{base_command} {' '.join(placeholders)}"
+
+class RenkuWorkflowBuilder:
+    def __init__(self, name):
+        self.name = name
+        self.steps = OrderedDict()
+
+    def add_step(self, step_name, base_command, inputs=None, outputs=None, parameters=None):
+        command = generate_command(base_command, inputs, outputs,parameters)
+        step = {
+            'command': command
+        }
+        if inputs:
+            step['inputs'] = [{key: value} for key, value in inputs]
+        if outputs:
+            step['outputs'] = [{key: value} for key, value in outputs]
+        if parameters:
+            step['parameters'] = [{key: value} for key, value in parameters] 
+        self.steps[step_name] = step
+
+    @staticmethod
+    def parse_workflow(yaml_content: str):
+        data = yaml.safe_load(yaml_content)
+        builder = RenkuWorkflowBuilder(data['name'])
+
+        for step_name, step_def in data['steps'].items():
+            command = step_def.get('command')
+            inputs = step_def.get('inputs', [])
+            outputs = step_def.get('outputs', [])
+            parameters = step_def.get('parameters', [])
+            builder.steps[step_name] = {
+                'command': command,
+                'inputs': inputs,
+                'outputs': outputs,
+                'parameters': parameters
+            }
+        return builder
+
+    @staticmethod
+    def from_file(filepath):
+        if not os.path.exists(filepath):
+            return None
+        with open(filepath, 'r') as f:
+            return RenkuWorkflowBuilder.parse_workflow(f.read())
+
+    def to_dict(self):
+        for step_name, step_value in self.steps.items():
+            for segment in ['inputs','outputs']:
+                for item in step_value.get(segment,[]):# ['inputs', 'outputs']:
+                    # Go over either inputs or outputs
+                    for name, value in item.items():
+                        if not isinstance(value, dict):
+                            raise ValueError(f"Invalid input. Step {step_name} must have {segment} of either dict or str type.")
+                        if isinstance(value, str):
+                            continue
+                        if isinstance(value, dict) and 'path' in value.keys():
+                            value['path'] = value['path'].replace(os.sep, '/')
+
+        return {
+            'name': self.name,
+            'steps': { key : value for key, value in self.steps.items()}
+        }
+
+    def to_yaml(self):
+        return yaml.dump(self.to_dict(), sort_keys=False)
+
+    def append_from(self, other, force=False):
+        if other.name != self.name:
+            raise ValueError(f"Cannot merge workflows with different names: {self.name} != {other.name}")
+
+        for step_name, step_def in other.steps.items():
+            if step_name in self.steps:
+                if force:
+                    print(f"[Overwriting] Step '{step_name}' was overwritten as 'force=True'.")
+                    self.steps[step_name] = step_def
+                else:
+                    print(f"[Skipping] Step '{step_name}' already exists. Use 'force=True' to overwrite.")
+            else:
+                self.steps[step_name] = step_def
+
+    def save_to_file(self, directory):
+        os.makedirs(directory, exist_ok=True)
+        filepath = os.path.join(directory, f"{self.name}.yaml")
+
+        if os.path.exists(filepath):
+            existing = RenkuWorkflowBuilder.from_file(filepath)
+            if existing and existing.name == self.name:
+                existing.append_from(self)
+                with open(filepath, 'w') as f:
+                    f.write(existing.to_yaml())
+                return
+        # Save as new
+        with open(filepath, 'w') as f:
+            f.write(self.to_yaml())
+
diff --git a/workflows/workflow_acsm_data_PAY_2024.yaml b/workflows/workflow_acsm_data_PAY_2024.yaml
new file mode 100644
index 0000000..2c55408
--- /dev/null
+++ b/workflows/workflow_acsm_data_PAY_2024.yaml
@@ -0,0 +1,184 @@
+name: workflow_acsm_data_PAY_2024
+steps:
+  update_datachain_params:
+    command: python $script_py $campaign_data_h5 $instrument_folder
+    inputs:
+    - script_py:
+        path: pipelines/steps/update_datachain_params.py
+    - campaign_data_h5:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06.h5
+    - in_1:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE/2024/params/calibration_params.yaml
+        implicit: true
+    - in_2:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE/2024/params/limits_of_detection.yaml
+        implicit: true
+    - in_3:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE/2024/params/validity_thresholds.yaml
+        implicit: true
+    outputs:
+    - out_1:
+        path: pipelines/params/calibration_params.yaml
+        implicit: true
+    - out_2:
+        path: pipelines/params/limits_of_detection.yaml
+        implicit: true
+    - out_3:
+        path: pipelines/params/validity_thresholds.yaml
+        implicit: true
+    parameters:
+    - instrument_folder:
+        value: ACSM_TOFWARE/2024
+  apply_calibration_factors:
+    command: python $script_py $campaign_data_h5 $calib_yaml
+    inputs:
+    - script_py:
+        path: pipelines/steps/apply_calibration_factors.py
+    - campaign_data_h5:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06.h5
+    - calib_yaml:
+        path: pipelines/params/calibration_factors.yaml
+    - data_descriptor_yaml:
+        path: campaignDescriptor.yaml
+        implicit: true
+    outputs:
+    - out_1:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibrated.csv
+        implicit: true
+    - out_2:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibrated_err.csv
+        implicit: true
+    - out_3:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibration_factors.csv
+        implicit: true
+    parameters: []
+  generate_flags_diagnostics:
+    command: python $script_py $data_file $flag_type
+    inputs:
+    - script_py:
+        path: pipelines/steps/generate_flags.py
+    - data_file:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06.h5
+    - validity_thresholds_yaml:
+        path: pipelines/params/validity_thresholds.yaml
+        implicit: true
+    outputs:
+    - flags_csv:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_meta_flags.csv
+        implicit: true
+    parameters:
+    - flag_type:
+        value: diagnostics
+  generate_flags_species:
+    command: python $script_py $data_file $flag_type
+    inputs:
+    - script_py:
+        path: pipelines/steps/generate_flags.py
+    - data_file:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06.h5
+    - calibration_params_yaml:
+        path: pipelines/params/calibration_params.yaml
+        implicit: true
+    - flag_in_0:
+        description: automated or cpc flag
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_meta_flags.csv
+        implicit: true
+    outputs:
+    - flags_csv:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_timeseries_flags.csv
+        implicit: true
+    parameters:
+    - flag_type:
+        value: species
+  prepare_ebas_submission:
+    command: python $script_py $in_1 $in_2 $in_3 $in_4 $month_range
+    inputs:
+    - script_py:
+        path: pipelines/steps/prepare_ebas_submission.py
+    - in_1:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibrated.csv
+    - in_2:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibrated_err.csv
+    - in_3:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibration_factors.csv
+    - in_4:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_timeseries_flags.csv
+    - lod:
+        path: pipelines/params/"limits_of_detection.yaml
+        implicit: true
+    - station:
+        path: pipelines/params/"station_params.yaml
+        implicit: true
+    outputs:
+    - out_1:
+        path: data/PAY_ACSM-092_2024.txt
+        implicit: true
+    - out_2:
+        path: data/PAY_ACSM-092_FLAGS_2024.txt
+        implicit: true
+    parameters:
+    - month_range:
+        value: 2-3
+  visualize_diagnostic_variables:
+    command: python $script_py $data_file $dataset_name $flags_dataset_name $x_var
+      $y_vars $fig_0_VaporizerTemp_C $fig_1_FlowRate_ccs $fig_2_FilamentEmission_mA
+      $fig_3_ABsamp
+    inputs:
+    - script_py:
+        path: pipelines/steps/visualize_datatable_vars.py
+    - data_file:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06.h5
+    - alternative_flags_csv:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_meta_flags.csv
+        implicit: true
+    outputs:
+    - fig_0_VaporizerTemp_C:
+        path: figures/fig_0_VaporizerTemp_C.html
+    - fig_1_FlowRate_ccs:
+        path: figures/fig_1_FlowRate_ccs.html
+    - fig_2_FilamentEmission_mA:
+        path: figures/fig_2_FilamentEmission_mA.html
+    - fig_3_ABsamp:
+        path: figures/fig_3_ABsamp.html
+    parameters:
+    - dataset_name:
+        value: ACSM_TOFWARE/2024/ACSM_PAY_2024_meta.txt/data_table
+    - flags_dataset_name:
+        value: ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_meta.txt/data_table
+    - x_var:
+        value: t_base
+    - y_vars:
+        value:
+        - VaporizerTemp_C
+        - FlowRate_ccs
+        - FilamentEmission_mA
+        - ABsamp
+  workflow_acsm_data_PAY_2024_step:
+    command: python $script_py $in_1 $in_2 $in_3 $in_4 $month_range
+    inputs:
+    - script_py:
+        path: pipelines/steps/prepare_ebas_submission.py
+    - in_1:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibrated.csv
+    - in_2:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibrated_err.csv
+    - in_3:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_processed/2024/ACSM_PAY_2024_timeseries_calibration_factors.csv
+    - in_4:
+        path: data/collection_PAY_2024_2025-06-06_2025-06-06/ACSM_TOFWARE_flags/2024/ACSM_PAY_2024_timeseries_flags.csv
+    - lod:
+        path: pipelines/params/"limits_of_detection.yaml
+        implicit: true
+    - station:
+        path: pipelines/params/"station_params.yaml
+        implicit: true
+    outputs:
+    - out_1:
+        path: data/PAY_ACSM-092_2024.txt
+        implicit: true
+    - out_2:
+        path: data/PAY_ACSM-092_FLAGS_2024.txt
+        implicit: true
+    parameters:
+    - month_range:
+        value: 2-3