Skip to main content

Evaluation of Covid-19 Ontologies Through OntoMetrics and OOPS! Tools

  • Conference paper
  • First Online:
Expert Clouds and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 444))

Abstract

Ontology provides a way to encode human intelligence so that machines can understand and make decisions by referring to this intelligence. For this reason, ontologies are used in every domain, specifically in the domains that relate to the emergency situation. Covid-19 became a serious concern and emerged as the most significant emergency for the world. Many Covid-19 ontologies are available on the Web to analyse the Covid-19 data semantically. However, a few questions arise from work done so far: How many Covid-19 ontologies are available? Which is a good Covid-19 ontology in terms of richness? What is the pitfall rate of the available Covid-19 ontologies? This paper focuses on these questions by providing a comprehensive survey on available Covid-19 ontologies. By this paper, analysts and researchers find a road map, an overview of research work that exists in terms of Covid-19 ontologies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. A. Patel, N.C. Debnath, A.K. Mishra, S. Jain, Covid19-IBO: A Covid-19 impact on Indian banking ontology along with an efficient schema matching approach. N. Gener. Comput. 39(3), 647–676 (2021)

    Article  Google Scholar 

  2. M. Horridge, H. Knublauch, A. Rector, R. Stevens, C. Wroe, A practical guide to building OWL ontologies using the Protégé-OWL plugin and CO-ODE tools edition 1.0. Univ. Manchester (2004)

    Google Scholar 

  3. A. Patel, S. Jain, Ontology versioning framework for representing ontological concept as knowledge unit, in International Semantic Intelligence Conference, vol. 2786 (2021)

    Google Scholar 

  4. A. González-Eras, R. Dos Santos, J. Aguilar, A. Lopez, Ontological engineering for the definition of a COVID-19 pandemic ontology. Inform. Med. Unlocked 100816 (2021)

    Google Scholar 

  5. J. Kachaoui, J. Larioui, A. Belangour, Towards an ontology proposal model in data lake for real-time COVID-19 cases prevention (2020)

    Google Scholar 

  6. J.V. Fonou-Dombeu, T. Achary, E. Genders, S. Mahabeer, S.M. Pillay, COVIDonto: An ontology model for acquisition and sharing of COVID-19 data, in International Conference on Model and Data Engineering (Springer, Cham, 2021), pp. 227–240

    Google Scholar 

  7. Y. Sayeb, M. Jebri, H.B. Ghezala, Managing COVID-19 crisis using C3HIS ontology. Procedia Comput. Sci. 181, 1114–1121 (2021)

    Article  Google Scholar 

  8. K.M. Kouamé, H. Mcheick, An ontological approach for early detection of suspected COVID-19 among COPD patients. Appl. Syst. Innovation 4(1), 21 (2021)

    Article  Google Scholar 

  9. A. Ahmad, M. Bandara, M. Fahmideh, H.A. Proper, G. Guizzardi, J. Soar, An overview of ontologies and tool support for COVID-19 analytics, in 2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW) (IEEE, 2021), pp. 1–8

    Google Scholar 

  10. J. Raad, C. Cruz, A survey on ontology evaluation methods, in Proceedings of the International Conference on Knowledge Engineering and Ontology Development, Part of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (2015).

    Google Scholar 

  11. M. Poveda-Villalón, A. Gómez-Pérez, M.C. Suárez-Figueroa, Oops!(ontology pitfall scanner!): An on-line tool for ontology evaluation. Int. J. Semant. Web Inf. Syst. (IJSWIS) 10(2), 7–34 (2014)

    Article  Google Scholar 

  12. A. Lozano-Tello, A. Gómez-Pérez, Ontometric: A method to choose the appropriate ontology. J. Database Manag. (JDM) 15(2), 1–18 (2004)

    Article  Google Scholar 

  13. R. Iqbal, M.A.A. Murad, A. Mustapha, N.M. Sharef, An analysis of ontology engineering methodologies: A literature review. Res. J. Appl. Sci. Eng. Technol. 6(16), 2993–3000 (2013)

    Article  Google Scholar 

  14. M.C. Suárez-Figueroa, A. Gómez-Pérez, M. Fernandez-Lopez, The NeOn methodology framework: A scenario-based methodology for ontology development. Appl. Ontol. 10(2), 107–145 (2015)

    Article  Google Scholar 

  15. B. Dutta, U. Chatterjee, D.P. Madalli, YAMO: yet another methodology for large-scale faceted ontology construction. J. Knowl. Manag. (2015)

    Google Scholar 

  16. S. Peroni, SAMOD: an agile methodology for the development of ontologies (2016)

    Google Scholar 

  17. CODO Ontology, https://bioportal.bioontology.org/ontologies/CODO

  18. COKPME Ontology, https://bioportal.bioontology.org/ontologies/COKPME

  19. COVID19 Ontology, https://bioportal.bioontology.org/ontologies/COVID19

  20. LONGCOVID Ontology, https://bioportal.bioontology.org/ontologies/LONGCOVID

  21. IDO-COVID-19 Ontology, https://bioportal.bioontology.org/ontologies/IDO-COVID-19

  22. COVIDCRFRAPID Ontology, https://bioportal.bioontology.org/ontologies/COVIDCRFRAPID

  23. COVID-19 Ontology, https://bioportal.bioontology.org/ontologies/COVID-19

  24. COVID-19-ONT-PM Ontology, https://bioportal.bioontology.org/ontologies/COVID-19-ONT-PM

  25. CIDO Ontology, https://bioportal.bioontology.org/ontologies/CIDO

Download references

Acknowledgements

This research is financially supported by Eastern International University, Binh Duong Province, Vietnam.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Archana Patel .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Debnath, N.C., Patel, A., Mazumder, D., Manh, P.N., Minh, N.H. (2022). Evaluation of Covid-19 Ontologies Through OntoMetrics and OOPS! Tools. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Expert Clouds and Applications. Lecture Notes in Networks and Systems, vol 444. Springer, Singapore. https://doi.org/10.1007/978-981-19-2500-9_25

Download citation

Publish with us

Policies and ethics