Poster

Gerardo Algara-Siller (FU Berlin), J. Marquardt, C.T. Koch, S. Reich

The Collaborative Research Centre 1772 generates heterogeneous and rapidly growing research data across multiple disciplines using a variety of methods and instruments. To keep these data transparent, reproducible, reusable, exchangeable, and suitable for long-term preservation, we have developed a Research Data Management (RDM) strategy that translates FAIR principles and DFG good-scientific-practice requirements into practical, project-level routines.

The strategy focuses on embedding RDM into daily scientific work rather than treating it as a final publication step. It addresses four interconnected areas: data description, data quality, data handling, and data exchange. Standardised documentation practices will be introduced through file-naming conventions, manifest templates, metadata directives, controlled vocabularies, schemas and scripts specific for the CRC. These measures strengthen the description, provenance, and interpretability of research data from the moment of creation.

The open file format HDF5 is promoted as the priority format for storage, exchange, and archival, and will be supported with either embedded metadata or following a CRC-specific pseudo-NeXus application definition to improve interoperability across data types and experimental contexts.

The strategy also establishes infrastructure and literacy measures for a large collaborative project environment. An optimized instance of NOMAD Oasis (from FAIRmat e.V.) will be deployed as a trusted platform for data exchange, publication, and archival, while templates, automation scripts, metadata-extraction tools, and instrument inventory will reduce manual workload. Continuous training on standardize documentation and broader RDM topics will build sustainable competencies within the centre.

By integrating this scalable RDM framework into our workflows, CRC 1772 is not just advancing Science, we are also building the foundation for a culture of collaboration, accountability, and long-term impact. Together, we are turning our scientific data into a lasting resource, ensuring that today’s research fuels tomorrow’s discoveries with accessible and reusable knowledge.