Understanding the Gap Between Information Models and Realism-Based Ontologies Using the Generic Component Model.

Journal: Studies in health technology and informatics
Published Date: Oct 27, 2021

Abstract

The wide-spread use of Common Data Models and information models in biomedical informatics encourages assumptions that those models could provide the entirety of what is needed for knowledge representation purposes. Based on the lack of computable semantics in frequently used Common Data Models, there appears to be a gap between knowledge representation requirements and these models. In this use-case oriented approach, we explore how a system-theoretic, architecture-centric, ontology-based methodology can help to better understand this gap. We show how using the Generic Component Model helps to analyze the data management system in a way that allows accounting for data management procedures inside the system and knowledge representation of the real world at the same time.

Authors

  • Mathias Brochhausen
    Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
  • Sarah J Bost
    Dept. of Health Outcomes and Biomedical Informatics, University of Florida, USA.
  • Nitya Singh
    Emerging Pathogens Institute & Dept. of Animal Sciences, University of Florida, USA.
  • Christoph Brochhausen
    Institute of Pathology & Central Biobank, University and University Clinic of Regensburg, Regensburg, Germany.
  • Bernd Blobel
    Medical Faculty, University of Regensburg, Germany.

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