In the area of research data management, we develop routines for managing research and development data according to the FAIR principle. FAIR stands for Findable, Accessible, Interoperable, and Reusable. Our goal is to describe research and development data using meaningful metadata and a consistent vocabulary that is machine- and human-readable, to store it securely, and to link it intelligently.
Our first step is data curation, where we ensure that all collected data is correctly and completely recorded and cataloged. By digitizing our laboratory processes, we achieve a comprehensive digital description that ensures the findability of the data.
The accessibility (Accessible) of our data is particularly important to us. We create data platforms and connect them to data rooms to enable easy and secure access to the data with appropriate rights management. In doing so, we implement the applicable research data policies, for example those of the DFG or the EU, and ensure the security of the data.
Another important aspect of our work is the interoperability (Interoperable) of data. By using standards and ontologies, we ensure a semantically consistent description of processes and models. This includes the description of the metadata. This enables us to link and process data from different sources (Linked Data).
Finally, we strive to make our data reusable. We ensure data quality and integrity and prepare and document the data in such a way that it can be easily used by other researchers.