Evaluating Clinical-Care Metadata Share and its FAIRification using the REA Ontology

Syeda A. Sohail*, Faiza A. Bukhsh*, Maurice van Keulen, Johannes G. Krabbe, Pavel Hruby

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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The FAIRification of data facilitates a fast-paced, global, FAIR metadata availability across domains for the sustainable growth of public/private organizations. Likewise, in healthcare, the clinical labs aim to achieve FAIR (biosample) metadata by keeping patient-specific infectious disease records. However, the responsible evaluation of the FAIRification process of Dutch clinical lab metadata is lacking at the local and global levels. From a responsible data science perspective, we normatively (in-principle) and empirically (in-practice) evaluate the Dutch clinical lab metadata share against FACT principles. The normative evaluation involved content analysis of FAIR concerning peer-reviewed publications and official websites. The empirical evaluation comprised a documentation review of standardized (public/confidential) documents regarding the metadata share of Dutch clinical labs. The evaluations assisted us in formulating two REA models based on REA ontology. The first REA model depicts the clinical lab metadata production run at a local/national level. The second REA model specifies the work (flow) breakdown structure of global FAIRification for FHIR Netherland using linkage relationship against FACT principles. In-field (IT and REA ontology) experts further evaluated the REA models for functional and structural veracity. Furthermore, our evaluations verified the presence of an underlying privacy-utility tradeoff in FAIRification of clinical lab metadata where data utility is prioritized over data protection.
Original languageEnglish
Title of host publicationVMBO 2022, Value Modelling and Business Ontologies 2022
Subtitle of host publicationProceedings of the 16th International Workshop on Value Modelling and Business Ontologies (VMBO 2022), held in conjunction with the 34th International Conference on Advanced Information Systems Engineering (CAiSE 2022), June 06–10, 2022, Leuven, Belgium
EditorsHans Weigand, Tiago Prince Sales, Paul Johanesson
Number of pages11
Publication statusPublished - 17 Jun 2022
Event16th International Workshop on Value Modelling and Business Ontologies, VMBO 2022 - Maria-Theresiacollege, Leuven, Belgium
Duration: 6 Jun 20226 Jun 2022
Conference number: 16

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


Workshop16th International Workshop on Value Modelling and Business Ontologies, VMBO 2022
Abbreviated titleVMBO
OtherThe importance of modeling the essence of enterprises on a level that abstracts from operational details is increasingly recognized. Two established enterprise modeling approaches are value modeling and business ontology. Value modeling is a business modeling approach that focuses on the value objects exchanged in business networks. Business ontology provides abstract descriptions of enterprises in their business context, focusing on what is needed to create and transfer value. Research in these fields is conducted using instruments like the REA Ontology (Resources, Events, Agents), the Unified Foundational Ontology (UFO), the Business Model Canvas, the e3value toolset, the Value Delivery Modeling Language (VDML), and the Enterprise Engineering framework.

The goal of the VMBO workshop series is two-fold. First, it aims to bring together researchers with an interest in value modeling and business ontology to present and discuss the current state of the art. Second, it aims to identify key areas for further research.
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  • FAIRification
  • Data protection
  • Data utility
  • Responsible Data Science
  • Dutch clinical care
  • FACT
  • REA ontology


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