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Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases

Gerhard Mayer, Wolfgang G. Müller, Karin Schork, Julian Uszkoreit, Andreas Weidemann, Ulrike Wittig, Maja Rey, Christian Quast, Janine Felden, Frank Oliver Glöckner, Matthias Lange, Daniel Arend, Sebastian Beier, Astrid Junker, Uwe Scholz, Danuta Schüler, Hans A. Kestler, Daniel Wibberg, Alfred Pühler, Sven Twardziok, Jürgen Eils, Roland Eils, Steve Hoffmann, Martin Eisenacher, Michael Turewicz

2021Briefings in Bioinformatics29 citationsDOIOpen Access PDF

Abstract

This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusable) data principles in a large distributed bioinformatics infrastructure. We address the challenge of heterogeneity of wet lab technologies, data, metadata, software, computational workflows and the levels of implementation and monitoring of FAIR principles within the different bioinformatics sub-disciplines joint in de.NBI. On the one hand, this broad service landscape and the excellent network of experts are a strong basis for the development of useful research data management plans. On the other hand, the large number of tools and techniques maintained by distributed teams renders FAIR compliance challenging.

Topics & Concepts

GermanComputer scienceData miningGeographyArchaeologyResearch Data Management PracticesScientific Computing and Data ManagementBiomedical Text Mining and Ontologies
Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases | Litcius