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Assessing the value of ontologically unpacking a conceptual model for human genomics

  • Alberto García Simon
  • , Anna Bernasconi
  • , Giancarlo Guizzardi
  • , Oscar Pastor
  • , Veda C. Storey
  • , José Ignacio Panach

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Although the knowledge about human genomics is available to all scientists, information about this scientific breakthrough can often be difficult to fully comprehend and share. A Conceptual Schema of the Human Genome was previously developed to assist in describing human genome-related knowledge, by representing a holistic view of the relevant concepts regarding its biology and underlying mechanisms. This model should become helpful for any researcher who works with human genomics data. We, therefore, perform the process of ontological unpacking on a portion of the model, to facilitate domain understanding and data exchange among heterogeneous systems. The ontological unpacking is a transformation of an input conceptual model into an enriched model based on a foundational ontology. The preliminary analysis and enrichment process are supported by the ontological conceptual modeling language OntoUML, which has been applied previously to complex models to gain ontological clarity. The value of the used method is first assessed from a theoretical point of view: the transformation results in significant, diverse modeling implications regarding the characterization of biological entities, the representation of their changes over time, and, more specifically, the description of chemical compounds. Since the ontological unpacking process is costly, an empirical evaluation is conducted to study the practical implications of applying it in a real learning setting. A particularly complex domain such as metabolic pathways is either described by adopting a traditional conceptual model or explained through an ontologically unpacked model obtained from a traditional model. Our research is evidence that including a strong ontological foundation in traditional conceptual models is useful. It contributes to designing models that convey biological domains better than the original models.
Original languageEnglish
Article number102242
JournalInformation systems
Volume118
DOIs
Publication statusPublished - 1 Sept 2023

Keywords

  • Ontological unpacking
  • Conceptual modeling
  • Foundational ontology
  • OntoUML
  • Genomics
  • Metabolic pathways
  • Data explanation
  • UT-Hybrid-D

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