Research data management (RDM) encompasses the processes of transformation, selection and storage of research data with the common goal of keeping them accessible, reusable and verifiable in the long term and independent of individuals (forschungsdaten.info).
The current RDM strategy and data guidelines for the Cluster of Excellence IntCDC are continuously being further developed. We consider it as a fundamental task of RDM to advice, train, and inform researchers on issues related to research data, in particular on questions of data storage, data documentation and making data accessible. Thereby, we acknowledge legal requirements on the one hand, and open-science practices on the other (e.g. FAIR Guideline Principles). According to IntCDC's research data policy, the goal is that each publication should be accompanied by a corresponding published dataset. IntCDC researchers are supported in designing sustainable research software, what is part of research software engineering (RSE). Needs-based training at a scientific level is designed, enabling researchers to develop and deliver software in a sustainable manner. Additionally, quality criteria for the recognition of research data and research software as a full publication at the University of Stuttgart are developed.
