Bioimaging Data Management Workflow for Plasma Medicine

This repository contains the Jupyter notebook implementation of a bioimaging data management workflow for plasma medicine (see preprint and poster). The workflow is implemented as a structured pipeline integrating open-source tools, including OMERO for image data management, eLabFTW as an electronic laboratory notebook, Adamant for schema-driven metadata collection, and Micro-Meta App for standardized documentation of microscopy acquisition settings that are connected via programming interfaces to enable persistent linkage of metadata to image datasets using standardized annotations.

Set up

A JupyterLab environment is required to run the provided notebook. The workflow was designed and tested on Python 3.12.5. Follow the installation guideline for support.

Dependencies

The following list summarizes the key dependencies:

• Elabapi
• OMERO-py
• Openpyxl
• Pandas

Usage

To use the provided Jupyter notebook, download workflow.ipynb and the two Python scripts omerohandler.py and elabftwapihandler.py. These files must be located in the same working directory. To access the respective OMERO and eLabFTW instances, the host addresses must be adjusted in the respective handler scripts (see description below).

eLabFTW

The codeline (l. 43) in elabftwapihandler.py has to be changed:

configuration.host = 'hostAdress'

the 'hostAdress' variable has to be replaced by the actual host url adress of your eLabFTW instance.

OMERO

The codeline (l. 21) in omerohandler.py has to be changed:

conn = BlitzGateway(usrname, passwrd, host= hostAdress, port= hostPort, secure=True)

the 'hostAdress' variable has to be replaced by the actual host url adress of your OMERO instance.

The adjusted notebook can be accessed by opening the .ipynb file in a JupyterLab environment; in some local JupyterLab installations, double-clicking the downloaded, modified .ipynb file may be sufficient.

Support

If you find a bug or need help, please open an issue. When reporting a bug, include the version, OS, steps to reproduce, expected vs actual behavior, and any logs or screenshots.

How to cite

Ahmadi M, Wagner R, Bekeschus S, Becker MM, Bioimaging Data Management Workflow for Plasma Medicine. BioRxiv. 2026; DOI: 10.64898/2026.01.26.700509.

Grant information

The work is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – NFDI 46/1 – 501864659.