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@TECHREPORT{David:644992,
      author       = {David, Romain and Hienola, Anca and Schmidt-Tremmel,
                      Friederike and van der Lek, Iulianna and Nentwich, Melanie
                      and Bodera Sempere, Jordi and Kalaitzi, Vasso and Guerrieri,
                      Giovanni and Wolff-Boenisch, Bonnie and Guezennec, Cécile
                      and Draščić, Martina and Vipavc Brvar, Irena},
      othercontributors = {van der Lek, Iulianna},
      title        = {{D}3.2 {C}ompetence {C}entres concepts and activities
                      (pre)existing in {EOSC}},
      publisher    = {Zenodo},
      reportid     = {PUBDB-2026-00519},
      pages        = {1-40},
      year         = {2025},
      abstract     = {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.},
      cin          = {IT},
      cid          = {I:(DE-H253)IT-20120731},
      pnm          = {OSCARS - O.S.C.A.R.S. - Open Science Clusters’ Action for
                      Research and Society (101129751) / 899 - ohne Topic
                      (POF4-899)},
      pid          = {G:(EU-Grant)101129751 / G:(DE-HGF)POF4-899},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)29},
      doi          = {10.5281/ZENODO.17549886},
      url          = {https://bib-pubdb1.desy.de/record/644992},
}