Journal of Computing and Natural Science


Theoretical Framework of Knowledge Representation for Information Sharing



Journal of Computing and Natural Science

Received On : 10 August 2022

Revised On : 28 October 2022

Accepted On : 12 November 2022

Published On : 05 April 2023

Volume 03, Issue 02

Pages : 058-068


Abstract


Since information from enterprises should be shared and exchanged in order to be understood and recognized, whereby unambiguous and transparent data is considered a vital requirement, information sharing has become crucial to the correct use of information assets. Sharing information may be seen as the most significant component of a company. Sharing or integrating information is used to bring together seemingly unrelated bodies of knowledge in an effort to enhance creativity. Development and training programs, reports, Information Technology (IT) platforms, official papers, and collaborative teams are all instances of information integration. It is possible to boost product and service quality, customer service responsiveness, innovation, and environmental sustainability via pervasive information integration. In this article, we take a look back at the revolutionary idea underpinning internal communication networks for Knowledge Management (KM), and Knowledge Representation (KR).


Keywords


Knowledge Management (KM), Knowledge Representation (KR), Information Technology (IT).


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We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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Cite this article


Susan Bagatto, “Theoretical Framework of Knowledge Representation for Information Sharing”, Journal of Computing and Natural Science, vol.3, no.2, pp. 058-068, April 2023. doi: 10.53759/181X/JCNS202303006.


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© 2023 Susan Bagatto. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.