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@ARTICLE{Jannasch:293308,
      author       = {A. Jannasch and S. Tulok and C. W. Okafornta and T. Kugel
                      and M. Bortolomeazzi$^*$ and T. Boissonnet and C.
                      Schmidt$^*$ and A. Vogelsang and C. Dittfeld and S.-M.
                      Tugtekin and K. Matschke and L. Paliulis and C. Thomas and
                      D. Lindemann and G. Fabig and T. Müller-Reichert},
      title        = {{S}etting up an institutional {OMERO} environment for
                      bioimage data: {P}erspectives from both facility staff and
                      users.},
      journal      = {Journal of microscopy},
      volume       = {297},
      number       = {1},
      issn         = {0022-2720},
      address      = {Oxford [u.a.]},
      publisher    = {Wiley-Blackwell},
      reportid     = {DKFZ-2024-01866},
      pages        = {105-119},
      year         = {2025},
      note         = {2025 Jan;297(1):105-119},
      abstract     = {Modern bioimaging core facilities at research institutions
                      are essential for managing and maintaining high-end
                      instruments, providing training and support for researchers
                      in experimental design, image acquisition and data analysis.
                      An important task for these facilities is the professional
                      management of complex multidimensional bioimaging data,
                      which are often produced in large quantity and very
                      different file formats. This article details the process
                      that led to successfully implementing the OME Remote Objects
                      system (OMERO) for bioimage-specific research data
                      management (RDM) at the Core Facility Cellular Imaging
                      (CFCI) at the Technische Universität Dresden (TU Dresden).
                      Ensuring compliance with the FAIR (findable, accessible,
                      interoperable, reusable) principles, we outline here the
                      challenges that we faced in adapting data handling and
                      storage to a new RDM system. These challenges included the
                      introduction of a standardised group-specific naming
                      convention, metadata curation with tagging and Key-Value
                      pairs, and integration of existing image processing
                      workflows. By sharing our experiences, this article aims to
                      provide insights and recommendations for both individual
                      researchers and educational institutions intending to
                      implement OMERO as a management system for bioimaging data.
                      We showcase how tailored decisions and structured approaches
                      lead to successful outcomes in RDM practices.},
      keywords     = {FAIR principles (Other) / OMERO (Other) / bioimaging data
                      (Other) / imaging facility (Other) / research data
                      management (RDM) (Other)},
      cin          = {W192 / W650},
      ddc          = {570},
      cid          = {I:(DE-He78)W192-20160331 / I:(DE-He78)W650-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39275979},
      doi          = {10.1111/jmi.13360},
      url          = {https://inrepo02.dkfz.de/record/293308},
}