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Building Information Science ontology (OIS) with Methontology and Protégé

Sawsaa, Ahlam and Lu, Joan (2012) Building Information Science ontology (OIS) with Methontology and Protégé. Journal of Internet Technology and Secured Transactions (JITST), 1 (3/4). ISSN 2046-3723

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Abstract

Ontology is the backbone of the semantic web and can overcome semantic barriers. Domain ontology provides a common understanding of the knowledge of a particular domain. Information Science, meanwhile, is an interdisciplinary science that is yet to be defined. It is necessary to develop Ontology of Information Science (OIS) to represent the unified domain knowledge.
This paper presents a representation of specific domain knowledge by providing a definition, scope, and boundaries of Information Science (IS). The methodology followed is Methontology, which is based on the IEEE standard for the development of a software life-cycle process. The achieved results are Information Science OIS ontology has fourteen facets: actors, method, practice, studies, mediator, kinds, domains, resources, legislation, philosophy and theories, societal, tools, time and space. It provides broader base of classes to offer opportunity to enrich OIS ontology. Also, it could be a basis for multiple ontologies to be built. OIS is structured at class level and subclass but does not provide the individual level. The model was evaluated by domain experts based on specific criteria and using reasoner FaCT++ to check the ontology usefulness, and how it could be transferred into application ontology for Information Science education. The paper then discusses the OIS ontology, particularly its structure and development.

Item Type: Article
Subjects: Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Schools: School of Computing and Engineering
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing
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School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:
Depositing User: Ahlam Sawsaa
Date Deposited: 22 May 2013 09:41
Last Modified: 22 May 2013 09:41
URI: http://eprints.hud.ac.uk/id/eprint/17581

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