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    An Ontology for Open Government Data Business Model


    Zeleti, Fatemeh Ahmadi and Ojo, Adegboyega (2017) An Ontology for Open Government Data Business Model. In: Proceedings of the 10th International Conference on Theory and Practice of Electronic Governance. ACM Digital Library, pp. 195-203. ISBN 978-1-4503-4825-6

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    Abstract

    Despite the existence of number of well-known conceptualization in e-Business and e-Commerce, there have been no efforts so far to develop a detailed, comprehensive conceptualization for business model. Current business literature is replete with fragmented conceptualizations, which only partially describe aspects of a business model. In addition, the existing conceptualizations do not explicitly support the emerging phenomenon of open government data – an increasingly valuable economic and strategic resource. Consequently, no comprehensive, formal, executable open government data business model ontology exists, that could be directly leveraged to facilitate the design, development of an operational open data business model. This paper bridges this gap by providing a parsimonious yet sufficiently detailed, conceptualization and formal ontology of open government data business model for open data-driven organizations. Following the design science approach, we developed the ontology as a ‘design artefact’ and validate the ontology by using it to describe an open data business model of an open data-driven organization.
    Item Type: Book Section
    Keywords: Open government data; open data business model; open data-driven organization; formal conceptualization; e-Business ontology; e-Commerce ontology; business model ontology;
    Academic Unit: Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI
    Faculty of Social Sciences > School of Business
    Item ID: 15799
    Identification Number: 10.1145/3047273.3047327
    Depositing User: Adegboyega Ojo
    Date Deposited: 11 Apr 2022 15:18
    Publisher: ACM Digital Library
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/15799
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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