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| Talk (non-conference) (Other) | FZJ-2026-05209 |
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2026
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Please use a persistent id in citations: doi:10.34734/FZJ-2026-05209
Abstract: With this introduction to research data management (RDM), we would like to provide practical assistance for all stages of RDM to anyone who generates and/or wants to use research data, regardless of the type of data. We all should be able to understand essential RDM structures and handle data confidently, from creation and analysis to long-term storage. In summary, research data is a valuable resource and it is worth handling it carefully and sustainably. The professional management of research data is becoming increasingly important in science and is now strongly recommended or even required by many third-party funding bodies (DFG, BMFTR, BMWE, EU, etc.) for the approval of funding for new research projects. The main motivation for this is to create a comprehensive collection of research data, the production of which is primarily financed by public funds. The focus here is on good scientific practice and the traceability of research results. Another aim is enabling meaningful reuse, for example as training data in the field of machine learning (ML) or in applications involving artificial intelligence (AI). Another aspect is the conservation of resources, both financial and for the protection of the environment and the climate. Conducting experiments and computer simulations may require a lot of energy and thus contribute to increased CO2 emissions into the atmosphere. Science can make a contribution here by avoiding the repeated generation of existing data.
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Conference / Event
Open Science Week 2026 am Forschungszentrum Jülich
Open Science Week am FZJ, onlineonline, Germany, 19 Oct 2026 - 22 Oct 2026
(2026)
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