The SIG quality assurance and metrics for FAIR data provides and discusses standards, metrics and guidelines for organizing data curation based on existing best practices and the FAIR data principles. The SIG focuses on challenges and applications of quality assurance and metrics in the context of NFDI4Ing, but many issues are transferable and apply to many types of data and research data management processes. Furthermore, the methods and tools developed by NFDI4Ing for the self-organization and self-monitoring of quality and maturity of research data and data management processes require an ongoing exchange of experience between different national and international stakeholders. For this reason, close collaboration with researchers in other NFDI consortia and the larger scientific community is a major goal of the SIG.

For example, international preliminary work in the subfield of Data Management Plans (DPM) shows that researchers desire a subject-specific adaptation of DMP templates and existing tools (e.g. the Research Data Management Organiser – RDMO). Therefore, the SIG is active in the working group discipline-specific guidance for DMP of the Research Data Alliance.