Data and information management ST-LE-2026-03

by Prof. Frank Oliver Glöckner (Alfred-Wegener-Institut), Dr Ivaylo Kostadinov (GFBio e.V.)

Thursday Feb 26, 2026, 1:00 PM → 4:00 PM Europe/Berlin

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Motivation

A comprehensive management of research data is part of each research project and belongs to good scientific practice. It accompanies each phase of a research project – from the proposal phase via data acquisition and data analyses to the publication phase. The overall goal of research data management is the production of findable (F), accessible (A), Interoperable (I) and reusable (R) – FAIR - data sets.
A good stewardship of data (following the FAIR principles; Wilkinson et al., 2016) and an open data culture (Nosek et al., 2015) foster reproducibility as well as sustainability in science and makes up the fundament for data science applications.

Learning contents

• Research data: Data life cycle and accompanied challenges
• Data management plans (DMP)
• FAIR data principle
• Meta data: standardization and its significance
• Archiving, publication and citation of research data sets

Learning outcomes

Understanding for the significance of research data management and an overview about concepts and approaches.

Prior knowledge

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Further Reading

• Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
• Wilkinson, M. D. et al. Comment: A design framework and exemplar metrics for FAIRness. Sci. Data 5, 1–4 (2018).
• Hodson, S. et al. Turning FAIR data into reality: interim report from the European Commission Expert Group on FAIR data (Version Interim draft). Interim Rep. from Eur. Comm. Expert Gr. FAIR data (2018). https://doi.org/10.5281/zenodo.1285272
• Collins, S. et al. FAIR Data Action Plan. Interim Recomm. actions from Eur. Comm. Expert Gr. FAIR data 1–21 (2018). https://doi.org/10.5281/zenodo.1285290
• Wilkinson, M. D. et al. Interoperability and FAIRness through a novel combination of Web technologies. PeerJ Comput. Sci. 3, e110 (2017)
• Mons, B. et al. Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud. Inf. Serv. Use 37, 49–56 (2017).

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