GPT Onto: A New Beginning for Malaysia Gross Pollutant Trap Ontology
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GPT Onto: A New Beginning for Malaysia Gross Pollutant Trap Ontology

Authors: Chandrika M.J., Lariyah M.S., Alicia Y.C. Tang

Abstract:

Ontology is widely being used as a tool for organizing information, creating the relation between the subjects within the defined knowledge domain area. Various fields such as Civil, Biology, and Management have successful integrated ontology in decision support systems for managing domain knowledge and to assist their decision makers. Gross pollutant traps (GPT) are devices used in trapping and preventing large items or hazardous particles in polluting and entering our waterways. However choosing and determining GPT is a challenge in Malaysia as there are inadequate GPT data repositories being captured and shared. Hence ontology is needed to capture, organize and represent this knowledge into meaningful information which can be contributed to the efficiency of GPT selection in Malaysia urbanization. A GPT Ontology framework is therefore built as the first step to capture GPT knowledge which will then be integrated into the decision support system. This paper will provide several examples of the GPT ontology, and explain how it is constructed by using the Protégé tool.

Keywords: Gross pollutant Trap, Ontology, Protégé.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330061

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References:


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