| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01243 | |
| Number of page(s) | 13 | |
| DOI | https://doi.org/10.1051/epjconf/202533701243 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701243
Enhancing Data Management in Nuclear Physics through a F.A.I.R.- Compliant Metadata Schema
1 GSI Helmholtzzentrum für Schwerionenforschung GmbH, Planckstraße 1, 64291 Darmstadt, Germany
2 Facility for Antiproton and Ion Research in Europe (FAIR GmbH), Planckstraße 1, 64291 Darmstadt, Germany
* e-mail: i.knezevic@gsi.de
** e-mail: a.k.mistry@gsi.de
Published online: 7 October 2025
Within the field of experimental nuclear physics, steps are underway to further advance good Research Data Management practices. At the heart of this is the goal of generating well-described F.A.I.R.-level experimental data and ensuring compliance with these principles. Here, we describe the landscape of Research Data Management in the nuclear physics domain, with a focus on supporting future actions with a F.A.I.R.-compliant metadata schema prototype for the community. In this work, we present a prototype metadata schema and platform (NPPilot), developed to support F.A.I.R.-compliant metadata generation and management workflows in experimental nuclear physics. The schema’s nodal, multi-layered structure supports metadata enrichment across domains, and a user-friendly generator facilitates schema customisation and export in various formats. We detail the development process, key features, and potential applications. We also describe how NPPilot will serve as the foundation for further developments through the NAPMIX project, which aims to expand its scope to a broader range of research domains. An outlook is given toward broader expansion of the schema to cross-domain physics fields.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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