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Research Data Management

Reproducibility of experiments/analysis and re-useability of research data are central components for reaching the full potential of biomedical research projects. Here, research data management following the FAIR Principles plays a vital role. By establishing targeted structures, processes, and documentation for data creation, processing, analysis/use, access, and storage, the complete process is transparent and thus reproducible, and enables independent researchers to contribute.

In every research field, research data management gains increasing importance, challenging researchers, and research groups. This manifests itself in more demanding guidelines and requirements imposed in funded projects by public funding organizations like EU, BMBF, and DFG.

The Research Data Management Group of the Medical Faculty (RDMGMed) supports researches and research groups in all phases of their projects, from proposal to publication. Specifically, we provide consulting and training courses for research data management during the complete data life cycle, ranging from data creation, processing, documentation of meta-data and use, access, and storage. Typical topics are the creation of data management plans, techniques and tools for meta-data collection, identifying and using suitable terminologies for data documentation, tools for data administration and handling, and the identification of suitable open and quotable research data repositories.

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