Research Data Management
Open and FAIR research data
Open and FAIR research data are the foundation of scientific progress, thriving and sustainable economies, and evidence-based policymaking. They promote transparency, reproducibility, and collaboration, and are considered an integral part of good scientific practice. In addition, FAIR data increase the visibility and citation rate of scientific work and are increasingly required and recognized by funding institutions.
If you have any questions feel free to contact us.
Why data management is important to us
Open and findable, accessible, interoperable and reusable (FAIR) research data favour innovation and sustainable economic development and are essential for knowledge-based policymaking.
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Open Science is just science: Offene Daten sind ein zentraler Baustein von Open Science. Open Data is an important cornerstone of Open Science. Data are the foundation of evidence-based decision-making. FAIR and well-documented data will retain long-term relevance, enabling reanalysis as new scientific frameworks and discoveries emerge. Thus, publishing data early on in open access expedites the scientific progress through transparency, reproducibility, and collaboration.
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Good Research Practice is good data management: How we treat our data reflects the quality and ethics of our science. Organizing, documenting, storing, sharing, and preserving data are not just technical chores—they're essential for transparency, reproducibility, and integrity in research.
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FAIR Data publications are publications: Publication of data in open repositories alongside the corresponding research article increases the citation rate of the article by up to 25%. Additionally, funders encourage researchers to include FAIR data publications in their publication list when applying for funding.
How we do this:
Sustainable management of research data includes the documentation and secure data storage throughout the scientific process, long-term archiving and openly sharing research data in certified data repositories according to the FAIR and TRUST principles.
As per the mareXtreme research policy, we follow the DAM research data guideline. This includes project specific data management plans (Login required: LINK) and annotation of data with metadata and documentation early in the process (e.g. using the Ocean Science Information System, OSIS) and the Observation to Archive (O2A) Registry as part of the O2A-Dataflow-Frameworks.
Research data and processing tools are published in open access whenever possible. The following trusted data repositories are relevant to our research:
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PANGAEA: geo-referenced observation and measurement data, experimental data, some model data
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WDC-CLIMATE: Earth System model data
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Qualiservice: Qualitative social sciences data, e.g. interviews
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GESIS Datenarchiv: quantitative social sciences data
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European Nucleotide Archive: genetic sequences via GFBio submission service
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GitHub with Zenodo DOI: Software und Code
Data management in the DAM research mission mareXtreme along the research data lifecycle. Modified after Wittmann et al. 2025 (CC-BY 4.0)
Showcase of research results
The German Marine Data Portal provides a metadata catalogue of published datasets and other products (mareXtreme) and allows creating and visualizing mapped data products in viewers.
Contacts
Central research data management mareXtreme:
Research data management within the projects:
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ElbeXtreme: Dr. Kaveh Purkiani und Dr. Christian Senet
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MULTI-MAREX: Roberto Benavides und Dr. Ricarda Nielsen
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METAscales: Annika Klein
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PrimePrevention: Dr. Astrid Wittmann und Martin Engler
We provide individual advice for researchers and organize workshops on data management. We work in close collaboration with the DAM Core Area Data Management and Digitalization and the data management consultant for DAM research missions. We contributed to the recommendations for research data management in the DAM research missions and projects.
