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@ARTICLE{Avraam:300281,
      author       = {D. Avraam and R. C. Wilson and N. Aguirre Chan and S.
                      Banerjee and T. R. P. Bishop and O. Butters and T. Cadman
                      and L. Cederkvist and L. Duijts and X. Escribà Montagut and
                      H. Garner and G. Gonçalves and J. R. González and S.
                      Haakma and M. Hartlev and J. Hasenauer and M. Huth and E.
                      Hyde and V. W. V. Jaddoe and Y. Marcon and M. T. Mayrhofer
                      and F. Molnar-Gabor and A. S. Morgan and M. Murtagh and M.
                      Nestor and A.-M. Nybo Andersen and S. Parker$^*$ and A.
                      Pinot de Moira and F. Schwarz and K. Strandberg-Larsen and
                      M. A. Swertz and M. Welten and S. Wheater and P. Burton},
      title        = {{D}ata{SHIELD}: mitigating disclosure risk in a multi-site
                      federated analysis platform.},
      journal      = {Bioinformatics advances},
      volume       = {5},
      number       = {1},
      issn         = {2635-0041},
      address      = {Oxford},
      publisher    = {Oxford University Press},
      reportid     = {DKFZ-2025-00734},
      pages        = {vbaf046},
      year         = {2025},
      abstract     = {The validity of epidemiologic findings can be increased
                      using triangulation, i.e. comparison of findings across
                      contexts, and by having sufficiently large amounts of
                      relevant data to analyse. However, access to data is often
                      constrained by practical considerations and by ethico-legal
                      and data governance restrictions. Gaining access to such
                      data can be time-consuming due to the governance
                      requirements associated with data access requests to
                      institutions in different jurisdictions.DataSHIELD is a
                      software solution that enables remote analysis without the
                      need for data transfer (federated analysis). DataSHIELD is a
                      scientifically mature, open-source data access and analysis
                      platform aligned with the 'Five Safes' framework, the
                      international framework governing safe research access to
                      data. It allows real-time analysis while mitigating
                      disclosure risk through an active multi-layer system of
                      disclosure-preventing mechanisms. This combination of
                      real-time remote statistical analysis, disclosure prevention
                      mechanisms, and federation capabilities makes DataSHIELD a
                      solution for addressing many of the technical and regulatory
                      challenges in performing the large-scale statistical
                      analysis of health and biomedical data. This paper describes
                      the key components that comprise the disclosure protection
                      system of DataSHIELD. These broadly fall into three classes:
                      (i) system protection elements, (ii) analysis protection
                      elements, and (iii) governance protection
                      elements.Information about the DataSHIELD software is
                      available in https://datashield.org/ and
                      https://github.com/datashield.},
      cin          = {W620},
      ddc          = {004},
      cid          = {I:(DE-He78)W620-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40191546},
      pmc          = {pmc:PMC11968321},
      doi          = {10.1093/bioadv/vbaf046},
      url          = {https://inrepo02.dkfz.de/record/300281},
}