Ten years after the FAIR Principles were introduced, the challenge is no longer simply understanding why research data should be Findable, Accessible, Interoperable and Reusable. The greater challenge is implementing FAIR data management as part of everyday research practice.

A new publication in Scientific Data by our NFDI4BIOIMAGE Data Steward Mohsen Ahmadi, Markus Becker, and colleagues addresses this challenge for bioimaging in plasma medicine. In this field, microscopy images, biological information, plasma-treatment parameters, and microscopy metadata are often generated by different instruments, researchers, and software systems, making it difficult to maintain the connections between these data and to share them in a FAIR and reusable way.

Rather than developing another standalone solution, the authors present a practical, open-source workflow that integrates established research data management tools including OMERO, eLabFTW, Adamant, and the Micro-Meta App through a Jupyter Notebook. The workflow links imaging data with experimental context and structured metadata, supporting researchers in creating FAIR bioimaging datasets that can be more easily shared, discovered, and reused.

To further promote transparency and reproducibility, the dataset accompanying the publication has been deposited in the INPTDAT repository according to the FAIR principles, making the underlying bioimaging data openly available for reuse by the research community.

This work demonstrates how FAIR principles can be translated into practical, interoperable research workflows, helping make research data management an integral part of good scientific practice.

Publication: A FAIR bioimaging data management workflow for plasma medicine (Scientific Data)

https://www.nature.com/articles/s41597-026-07982-x

FAIR dataset (INPTDAT):

https://www.inptdat.de/dataset/bioimaging-data-management-workflow-plasma-medicine-dataset