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@INPROCEEDINGS{Sasse:1026700,
      author       = {Sasse, Julia and Darms, Johannes and Fluck, Juliane},
      title        = {{S}emantic {M}etadata {A}nnotation {S}ervice},
      reportid     = {FZJ-2024-03514},
      year         = {2022},
      abstract     = {Operationalising the FAIR (Findable, Accessible,
                      Interoperable, Reusable) guiding principles for scientific
                      data management and stewardship [1] enhance the use of data
                      beyond its original purpose. Data analysis of different
                      sources for example requires interoperability that allows
                      machines to automatically combine and process the data.
                      Semantic interoperability, i.e., the ability to
                      automatically interpret the shared information in a
                      meaningful way, is given special attention in the biomedical
                      domain. Its realization by ontology-based semantic
                      annotation is still a challenge due to various standards and
                      semantic richness of the data. Plenty semi-structured and
                      structured study documents exist that are not yet
                      semantically annotated. Despite of the laborious annotation
                      process, semantic annotation is largely done manually and
                      annotators have to manage data standards and formats as well
                      as a variety of complex terminologies and ontologies for
                      annotation. Therefore, a semi-automatic approach to support
                      researchers in semantic annotation and handling the
                      different data formats is desirable. In this context, the
                      National Research Data Infrastructure for Personal Health
                      Data (NFDI4Health) aims to improve the FAIR access to
                      structured health data originating from epidemiology
                      studies, public health and clinical studies and support the
                      harmonization of (meta-)data [2]. For the latter, we present
                      an approach for a cross-domain and extensible semantic
                      metadata annotation service, that addresses the problems
                      stated above. Basic requirements for the metadata annotation
                      service are an open accessible web service, open code and an
                      interface to integrate different terminology lookup services
                      with access to terminology concepts depending on the use
                      case. For the medical domain, support for the SNOMED
                      terminology and common standards such as HL7 FHIR [3] are
                      additional requirements. While some metadata annotation
                      services already exist (e.g. [4]), they are in many cases
                      tailored to specific data formats and terminologies or they
                      do not meet all basic prerequisites. A first prototype was
                      developed that meets the basic requirements and can be
                      adapted to specific use cases. Terminology search via the
                      Ontology Lookup Service [5] was implemented in an
                      open-source web application to provide access to a wide
                      range of terminologies. Usability tests with users indicated
                      a good user experience. Currently, the annotation service is
                      being further adapted for a use case in the medical domain.
                      Therefore, the HL7 FHIR standard will be integrated and the
                      SNOMED CT terminology will be used for semantic annotation
                      of medical terms. References [1 ] Wilkinson, M.D.;
                      Dumontier, M.; Aalbersberg, I.J.J.; Appleton, G.; Axton, M.;
                      Baak, A.; Blomberg, N.; Boiten, J.-W.; da Silva Santos,
                      L.B.; Bourne, P.E.; et al. The FAIR Guiding Principles for
                      Scientific Data Management and Stewardship. Sci Data 2016,
                      3, 160018, doi:10.1038/sdata.2016.18. [2] Fluck, J.;
                      Lindstädt, B.; Ahrens, W.; Beyan, O.; Buchner, B.; Darms,
                      J.; Depping, R.; Dierkes, J.; Neuhausen, H.; Müller, W.; et
                      al. NFDI4Health – Nationale},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.5281/ZENODO.6366013},
      url          = {https://juser.fz-juelich.de/record/1026700},
}