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InBiodiv-O: An Ontology for Biodiversity Knowledge Management

Author

Listed:
  • Archana Patel

    (Eastern International University, Vietnam)

  • Sarika Jain

    (National Institute of Technology, Kurukshetra, India)

  • Narayan C. Debnath

    (Eastern International University, Vietnam)

  • Vishal Lama

    (Amdocs Development Centre India LLP, India)

Abstract

To present the biodiversity information, a semantic model is required that connects all kinds of data about living creatures and their habitats. The model must be able to encode human knowledge for machines to be understood. Ontology offers the richest machine-interpretable semantics that are being extensively used in the biodiversity domain. Various ontologies are developed for the biodiversity domain; however, these ontologies are not capable to define the Indian biodiversity information though India is one of the megadiverse countries. To semantically analyze the Indian biodiversity information, it is crucial to build an ontology that describes all the terms of this domain. Since the curation of the ontology depends on the domain where these are used, there is no ideal methodology defined yet. The aim of this article is to develop an ontology that semantically encodes all the terms of Indian biodiversity information in all its dimensions based on the proposed methodology. The evaluation of the proposed ontology depicts that ontology is well built in the specified domain.

Suggested Citation

  • Archana Patel & Sarika Jain & Narayan C. Debnath & Vishal Lama, 2022. "InBiodiv-O: An Ontology for Biodiversity Knowledge Management," International Journal of Information System Modeling and Design (IJISMD), IGI Global, vol. 13(7), pages 1-18, October.
    • Handle: RePEc:igg:jismd0:v:13:y:2022:i:7:p:1-18
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISMD.315021
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    References listed on IDEAS

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    1. Adolfo Lozano-Tello & Asunción Gomez-Perez, 2004. "ONTOMETRIC: A Method to Choose the Appropriate Ontology," Journal of Database Management (JDM), IGI Global, vol. 15(2), pages 1-18, April.
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