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Research Conference on Metadata and Semantics Research

MTSR 2021: Metadata and Semantic Research pp 322–335Cite as

Ontology-Based Interestingness in COVID-19 Data

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1537))

Abstract

This paper describes an approach to mining interestingness in data by designing domain ontology, COKPME and populating it with anonymized COVID-19 data from private hospital in Karnataka State, India. In general, association rules applied to healthcare data generate a large number of rules. These generated rules may not guarantee interestingness of the generated knowledge. To address this, we propose an ontology-based interestingness measure using the association rule mining algorithm. With the association rule, the implicit relationship between different categories of data attributes is captured. Our approach is to design the domain ontology, populate with data instances and operate association rules for semantic and non-semantic data to discover interesting facts.

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Notes

  1. 1.

    https://schema.org/.

  2. 2.

    http://xmlns.com/foaf/spec/.

  3. 3.

    https://bioportal.bioontology.org/ontologies/COKPME.

  4. 4.

    https://bioportal.bioontology.org/ontologies/CODO.

  5. 5.

    https://www.dublincore.org/specifications/dublin-core/dcmi-terms/.

  6. 6.

    https://github.com/abhilashcb8/COKPME.

  7. 7.

    https://github.com/dgarijo/Widoco.

  8. 8.

    http://vowl.visualdataweb.org/webvowl.html.

  9. 9.

    https://github.com/abhilashcb8/COKPME.

  10. 10.

    https://www.ontotext.com/products/graphdb/.

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Acknowledgements

This work was supported in part by the Department of Health and Family Welfare Services (HFWS), Government of Karnataka, India. We also extend our special thanks to the E-Health section of HFWS, Government of Karnataka, India, for providing all the necessary support and encouragement.

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Authors and Affiliations

  1. Indian Institute of Information Technology Dharwad, Dharwad, India

    C. B. Abhilash & Kavi Mahesh

Authors
  1. C. B. Abhilash
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  2. Kavi Mahesh
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Correspondence to C. B. Abhilash .

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Editors and Affiliations

  1. International Hellenic University, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Complutense University of Madrid, Madrid, Spain

    María-Antonia Ovalle-Perandones

  3. University College London, London, UK

    Andreas Vlachidis

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Abhilash, C.B., Mahesh, K. (2022). Ontology-Based Interestingness in COVID-19 Data. In: Garoufallou, E., Ovalle-Perandones, MA., Vlachidis, A. (eds) Metadata and Semantic Research. MTSR 2021. Communications in Computer and Information Science, vol 1537. Springer, Cham. https://doi.org/10.1007/978-3-030-98876-0_28

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  • DOI: https://doi.org/10.1007/978-3-030-98876-0_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-98875-3

  • Online ISBN: 978-3-030-98876-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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