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dc.contributor.authorDong, Hai
dc.contributor.authorHussain, Farookh Khadeer
dc.contributor.authorChang, Elizabeth
dc.identifier.citationDong, Hai and Hussain, Farookh Khadeer and Chang, Elizabeth. 2011. ORPMS: An ontology-based real-time project monitoring system in the cloud. Journal of Universal Computer Science. 17 (8): pp. 1161-1182.

Project monitoring plays a crucial role in project management, which is a part of every stage of a project’s life-cycle. Nevertheless, along with the increasing ratio of outsourcing in many companies’ strategic plans, project monitoring has been challenged by geographically dispersed project teams and culturally diverse team members. Furthermore, because of the lack of a uniform standard, data exchange between various project monitoring software becomes an impossible mission. These factors together lead to the issue of ambiguity in project monitoring processes. Ontology is a form of knowledge representation with the purpose of disambiguation. Consequently, in this paper, we propose the framework of an ontology-based real-time project monitoring system (ORPSM), in order to, by means of ontologies, solve the ambiguity issue in project monitoring processes caused by multiple factors. The framework incorporates a series of ontologies for knowledge capture, storage, sharing and term disambiguation in project monitoring processes, and a series of metrics for assisting management of project organizations to better monitor projects. We propose to configure the ORPMS framework in a cloud environment, aiming at providing the project monitoring service to geographically distributed and dynamic project members with great flexibility, scalability and security. A case study is conducted on a prototype of the ORPMS in order to evaluate the framework.

dc.publisherSpringer-Verlag, Graz University
dc.subjectProduct Quality Evaluation
dc.subjectProject Progress Assessment
dc.subjectProject Management
dc.subjectProject Monitoring
dc.titleORPMS: An ontology-based real-time project monitoring system in the cloud
dc.typeJournal Article
dcterms.source.titleJournal of Universal Computer Science

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curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusOpen access

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