PuSH - Publication Server of Helmholtz Zentrum München

Inau, E.T.* ; Dedié, A.* ; Anastasova, I.* ; Schick, R.* ; Fröhlich, B.* ; Roden, M.* ; Birkenfeld, A.L. ; Hrabě de Angelis, M. ; Preusse, M.* ; Waltemath, D.* ; Zeleke, A.A.*

Lessons learned from implementing FAIRification workflows in diabetes research in Germany.

PLOS Digit Health 5:e0001139 (2026)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The FAIR principles guide data stewardship towards maximizing the value of scientific data while offering a high level of flexibility to accommodate differences in standards and scientific practices. Research communities have developed and implemented domain-specific workflows to make their data FAIR. This work compares the implementation of two externally developed structured FAIRification workflows-a generic workflow and a domain-specific workflow- using the example of metadata captured in diabetes research in Germany and applying the FAIR data maturity model developed by the Research Data Alliance. Interestingly, the implementation of both workflows required similar resources and led us to achieve the same FAIRness rating. We therefore conclude that the adaptations made in the FAIRification workflow for health research data improve efficiency but do not necessarily lead to higher FAIRness scores when applied to core data sets. Based on the results of our workflow comparison, we identified a list of requirements that should be met for the FAIRification of a core data set regardless of the workflow employed. In the future, FAIR data strategies and infrastructure should be planned and implemented as early as possible in the FAIRification journey. It is anticipated that this comparative analysis will help establish standard operating procedures for the FAIRification of core data sets for health studies.
Altmetric
Additional Metrics?
[➜Log in]
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Keywords Fair Data; Protection; Privacy
ISSN (print) / ISBN 2767-3170
e-ISSN 2767-3170
Journal PLOS Digital Health
Quellenangaben Volume: 5, Issue: 1, Pages: , Article Number: e0001139 Supplement: ,
Publisher Public Library of Science (PLoS)
Publishing Place 1160 Battery Street, Ste 100, San Francisco, Ca 94111 Usa
Reviewing status Peer reviewed
Institute(s) Institute of Diabetes Research and Metabolic Diseases (IDM)
Institute of Experimental Genetics (IEG)
Grants Deutsches Zentrum fr Diabetesforschung
NFDI4Health