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Complexity Based Analysis of eGov Ontologies

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Electronic Government and the Information Systems Perspective (EGOVIS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10441))

Abstract

The analysis of complexity of ontologies in a domain reveals their underlying characteristics and support their selection, reuse and maintenance. This study performs the analysis of e-government ontologies in the oeGov repository based on their complexity. The complexity metrics of oeGov ontologies are computed and analysed. Results revealed that only the top level ontologies in the oeGov architecture have classes, properties and instances; the majority of the constituents of the oeGov repository are instances or datasets of the top level ontologies. Results further revealed important facts on the distribution of relations and instances in the oeGov ontologies and portrayed that the government (gov) and geopolitical ontologies are the more complex ontologies in the oeGov repository.

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Authors and Affiliations

  1. Department of Software Studies, Vaal University of Technology, Private Bag X021, Andries Potgieter Blvd, Vanderbijlpark, 1900, South Africa

    Jean Vincent Fonou-Dombeu

  2. Department of ICT, Vaal University of Technology, Private Bag X021, Andries Potgieter Blvd, Vanderbijlpark, 1900, South Africa

    Yannick Kazela Kazadi

Authors
  1. Jean Vincent Fonou-Dombeu
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  2. Yannick Kazela Kazadi
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Correspondence to Jean Vincent Fonou-Dombeu .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Corvinus University of Budapest, Budapest, Hungary

    Andrea Kő

  2. Italian National Research Council, Institute of Legal Information Theory and Techniques, Florence, Italy

    Enrico Francesconi

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Fonou-Dombeu, J.V., Kazadi, Y.K. (2017). Complexity Based Analysis of eGov Ontologies. In: Kő, A., Francesconi, E. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2017. Lecture Notes in Computer Science(), vol 10441. Springer, Cham. https://doi.org/10.1007/978-3-319-64248-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-64248-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64247-5

  • Online ISBN: 978-3-319-64248-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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