Ontology within Faculty of Information Technology and Science Quantitative (FTMSK) knowledge repository / Suriyati Razali … [et al.]

• Main Authors: Razali, Surtyati, Nordin, Ariza, Abdullah, Natrah, Redzuan, Fauziah
• Format: Research Reports
• Language: English
• Published: 2006
• Subjects: Ontology; Electronic data processing. Information technology. Knowledge economy. Including artificial intelligence and knowledge management; Institutional repositories
• Online Access: https://ir.uitm.edu.my/id/eprint/49028/1/49028.pdf; https://ir.uitm.edu.my/id/eprint/49028/
• Institution: Universiti Teknologi Mara

The implication of information scarcity and unmanaged knowledge is an opportunity loss of organizations to gain competitive edge. In a knowledge-intensive organization such as a university faculty there is a pressing need to provide lecturers and administrators as well as policy makers and ultimately students with value-added services integrating information spread over distributed heterogeneous repositories into a centralized knowledge repository. Knowledge artifacts can be organized in the knowledge repositories either automatically or manually by users using organization taxonomy. In order to incorporate available knowledge artifacts of educational, research and quality programs into a powerful knowledge management system it is mandatory to identify and exploit their semantic relationship. For this purpose, we advocate an ontological approach that captures these relations that allows effective sharing and dissemination of knowledge artifacts. The ontological approach undertaken by this research, models the knowledge of the learning content and the lecturer's profile with ontologies whose vocabularies are inherited from standards situated on the Web as reference points to provide semantics. The research uncovers how ontologies can be used for integration, but it is not possible to have a single ontology for all the faculty's content and profiling organization structures. In addition the ontology evolution is crucial in any dynamic knowledge intensive environment. The initial version of the learning content ontology is presented as the core component of the faculty's knowledge repository adopting open source framework for the prototypal implementation to display the knowledge structure developed using Protege knowledge model.