Research data management
Research Data Management Freie Universität Berlin
Researchers are faced with the challenge of not only managing their research data, but also making it reusable. The long-term accessibility of research fundamentals and results is a quality feature of good scientific practice and sometimes a condition of project funding.
The prerequisites for sustainable research data management are standardised procedures, tools and established infrastructures.
Support
In order to support researchers in this process, Freie Universität is continuously expanding its consulting and training services for research data management. Basic information, tips and materials on the topic can be found on the website of the Research Data Management team at FU Berlin. You are also welcome to contact Andreas Hübner directly, who is in charge of the Department of Earth Sciences in the Research Data Management team (send E-Mail or phone: 030 838 71062).
Resources
Research data management- Practical advice from Freie Universität Berlin
- Detailed information at forschungsdaten.info (in German, with subject-specific website on the geosciences) or UK Data Service (in English)
- Guide with special reference to the management of qualitative data: Research Data Management for Small Research Projects - A practical guide (2023)
- NFDI4Earth Helpdesk: this service offers researchers in Earth System Sciences contact to a Germany-wide team of research data specialists to provide answers to your questions related to all aspects of research data management.
Please use this internet form to ask your question.
Central tasks of data management for researchers are the documentation of research data (incl. software). The two checklists linked below briefly present the most important points:
- Data Documentation and Citation Checklist (2023)
- Software Documentation and Citation Checklist (2023)
Research data policies for research projects are useful for establishing a common standard in a research project on how to deal with the research data generated in the project. This is particularly relevant in projects with many participants and when different research disciplines work together.