Towards FAIR fundamental physics: PUNCH4NFDI approach

Research data management is becoming increasingly important in data-intensive fundamental physics, including astroparticle, particle, nuclear and astrophysics. Growing data volumes and complexity, increasing interdisciplinarity, high costs of data acquisition and processing, and rising expectations for open science and AI-ready digital research outputs are driving these communities toward FAIR (Findable, Accessible, Interoperable, Reusable) data management practices. Key efforts in this direction include reuse and practical harmonisation of semantic artefacts such as metadata schemas, thesauri and controlled vocabularies; making explicit expert knowledge embedded in collaboration-internal data transformations, specialised software tools, and internal data formats (e.g., FITS, ROOT, HDF5); and defining minimal requirements for reusable digital research objects. This talk presents the multi-layer metadata model and the concept and the use-case-based implementations of Digital Research Product, developed within the PUNCH4NFDI (Particles, Universe, NuClei and Hadrons for the German National Research Data Infrastructure, punch4nfdi.de) consortium in the context of a modern FAIR Data landscape and as core elements of the PUNCH4NFDI Science Data Platform.