Learning Objectives Matrix on RDM - Community of Practice and Subject-specific Adaptations

Research data are generated across all scientific disciplines and form the foundation for knowledge, innovation, and societal progress. Effectively and sustainably managing them throughout the entire research data lifecycle requires not only technical infrastructures, but also targeted skills development and an active, collaborative Community of Practice (CoP). An example of such a CoP in the field of research data management (RDM) is the Sub-Working Group Training/Further Education [1] of the DINI/nestor Working Group Research Data. It provides a space for professional exchange, peer networking, and joint solution development. At the same time, it contributes to the establishment of practical tools and methods in RDM. A key result of this collaboration is the Learning Objectives Matrix (Lernzielmatrix, LZM) [2] – a tool for the systematic promotion of data literacy. First published in 2022, the LZM has since been iteratively developed through continuous community engagement. The third version, released in March 2025, includes updated content, an optimized structure, multilingual elements, and practice-oriented use cases. It addresses four key target groups – bachelor's and master's students, early career researchers, and data stewards – and covers relevant areas of research data management, including foundational knowledge, data handling, metadata, long-term archiving, publication, legal and ethical aspects, as well as meta-competencies such as consulting and teaching. The LZM has proven effective in a wide range of contexts – including NFDI consortia, data literacy centres, and various educational and training programs. Its modular design and generic content allow for flexible adaptation to disciplinary and institutional needs. The matrix is accompanied by a glossary that contextualizes key terms and will soon be available as multilingual Linked Open Data (LOD). This contribution presents the development, evolution, and adaptation of the LZM, highlights examples of its practical use, and discusses its integration into national and international RDM initiatives. Future perspectives will also be addressed, such as integrating critical thinking and sustainability into RDM, and making the LZM machine-readable to enhance interoperability and reuse. In line with the conference theme "RDM in Action", this contribution explores how an active, cross-disciplinary CoP can support the development of tools and methods that not only provide orientation but also offer concrete solutions for implementing good research data management. Finally, it reflects on the challenges and potential for the sustainable, collaborative advancement of the matrix – also in an international context.