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@ARTICLE{Mauer:285251,
      author       = {Mauer, Karoline and Iyappan, Anandhi and Parker, Simon and
                      Sürün, Bilge and Tremper, Galina and Menges, Paul and
                      Kuchenbecker, Léon and Kirli, Koray and Schultze, Joachim L
                      and Nahnsen, Sven and Ulas, Thomas},
      collaboration = {Consortium, GHGA},
      title        = {{S}emantic alignment of the {G}erman {H}uman
                      {G}enome-{P}henome {A}rchive metadata model in {E}urope's
                      genomics field.},
      journal      = {Scientific data},
      volume       = {13},
      number       = {1},
      issn         = {2052-4436},
      address      = {London},
      publisher    = {Nature Publ. Group},
      reportid     = {DZNE-2026-00193},
      pages        = {242},
      year         = {2026},
      abstract     = {Legal and technical developments drive data sharing via
                      federated infrastructures, especially in the field of human
                      omics. This requires interoperability across technical,
                      syntactic, organizational, and semantic layers. The German
                      Human Genome-Phenome Archive (GHGA) has been building a
                      national, federated infrastructure for secure sharing of
                      human omics data. As part of its mission to enhance
                      interoperability and to promote reliable data sharing, a
                      detailed crosswalk analysis was conducted comparing the GHGA
                      metadata model with four other domain-relevant standards and
                      metadata models: EGA (Submission API and model draft), FAIR
                      Genomes and ISA-tab. The analysis aimed at identifying
                      semantic consensus fields to define datasets in the context
                      of human omics by forward mapping (GHGA model to external
                      models). Backward mapping (external models to GHGA) focused
                      on spotting gaps in GHGA's semantic metadata representation.
                      Forward mapping showed overall similar property coverage
                      across models, aligning with MINSEQE. Backward mapping
                      showed greater model heterogeneity. None of the identified
                      information gaps spanned across all models. These findings
                      highlight the detail and adaptability of the GHGA metadata
                      model.},
      keywords     = {Humans / Metadata / Genomics / Genome, Human / Semantics /
                      Germany / Europe / Information Dissemination / Databases,
                      Genetic},
      cin          = {AG Schultze / PRECISE},
      ddc          = {500},
      cid          = {I:(DE-2719)1013038 / I:(DE-2719)1013031},
      pnm          = {354 - Disease Prevention and Healthy Aging (POF4-354) / 352
                      - Disease Mechanisms (POF4-352)},
      pid          = {G:(DE-HGF)POF4-354 / G:(DE-HGF)POF4-352},
      experiment   = {EXP:(DE-2719)PRECISE-20190321},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:41673046},
      pmc          = {pmc:PMC12905157},
      doi          = {10.1038/s41597-026-06575-y},
      url          = {https://pub.dzne.de/record/285251},
}