TY  - RPRT
AU  - David, Romain
AU  - Hienola, Anca
AU  - Schmidt-Tremmel, Friederike
AU  - van der Lek, Iulianna
AU  - Nentwich, Melanie
AU  - Bodera Sempere, Jordi
AU  - Kalaitzi, Vasso
AU  - Guerrieri, Giovanni
AU  - Wolff-Boenisch, Bonnie
AU  - Guezennec, Cécile
AU  - Draščić, Martina
AU  - Vipavc Brvar, Irena
TI  - D3.2 Competence Centres concepts and activities (pre)existing in EOSC
PB  - Zenodo
M1  - PUBDB-2026-00519
SP  - 1-40
PY  - 2025
AB  - This deliverable presents an overview of EOSC-related activities and projects that could be taken into account for the design and implementation of Competence Centres (CCs), positioned as key instruments to support data-intensive, FAIR-compliant, and interdisciplinary research within the European Open Science Cloud (EOSC). It synthesises existing practices, conceptual frameworks, and policy recommendations drawn from ongoing and past projects. CCs are understood by most of the research communities as decentralised, composable structures that may consolidate community expertise, support training and guidance for data sharing and reuse or provide embedded services across diverse research contexts. The deliverable outlines the different types of contributions of the domain-specific clusters. Each science cluster intends to align its CC strategies on either thematic priorities, governance approaches, training assets etc, and reflect on how they then could align within the OSCARS CC design and definition proposed in the framework of OSCARS WP1 (Bodera Sempere et al., 2024). The result of this landscaping highlights existing or in development principles, acknowledges heterogeneous implementations, foster cross-community learning and will lay the groundwork for a future inter-OSCARs project and inter-community paper on all kind of Competence Centres that can act in the framework of EOSC (discipline specific or thematic, local, regional, national…). The document identifies key interdisciplinary challenges such as multimodal data integration and large-scale metadata analysis emphasising the need for cultural change, capacity building, and embedded support mechanisms close to research practice, Challenges identified demand robust infrastructures, sustained collaboration, and the realisation of the “FAIR web of data,” a central EOSC ambition. The OSCARS CC model builds upon these insights to propose a federated and scalable ecosystem of competence. The models offer a practical roadmap to foster uptake, interoperability, and sustainability of Open Science across European research communities.
LB  - PUB:(DE-HGF)29
DO  - DOI:10.5281/ZENODO.17549886
UR  - https://bib-pubdb1.desy.de/record/644992
ER  -