Abstract
Ovitrap survey is one of dengue surveillance techniques employed by Ministry of Health Malaysia to identify current rate of vector population in a selected area. Result obtained from this activity is used to determine suitable control method to eradicate vector in the said area. This research study proposes a context-aware ontology that provides foundation of dengue surveillance system based on Ovitrap survey procedures exercised in Malaysia to assist entomologies on data analysis and decision-making. Ontology concepts are derived following guidelines provided by METHONTOLOGY methodology. The sub-activities of Ovitrap survey are categorized into two and formed two main concepts, which are field activities and lab activities. The other two main concepts represent instruments required to carry out Ovitrap survey and context information for the ontology. Context-awareness in ontology allows information flow and sharing between these main concepts. Result obtained could be used as support when requesting deployment of vector control activities. An entomologist expert validated the information flow of the proposed ontology while the ontology quality is measured following ontology quality metric suite. Accurate and correct representation of dengue surveillance activity via ontology could assist entomologist to carry out Ovitrap survey faster and easier.
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Acknowledgements
We would like to thank the Ministry of Education (MOE) Malaysia for sponsoring the research through the Fundamental Research Grant Scheme (FRGS) with vote number 5F080 and Universiti Teknologi Malaysia for providing the facilities and supporting the research. In addition, we would like to extend our gratitude to the lab members in the EReTSEL Lab, School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia for their invaluable ideas and support throughout this study.
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Zuki, S.Z.M., Mohamad, R., Sa’adon, N.A. (2020). Context-Aware Ontology for Dengue Surveillance. In: Saeed, F., Mohammed, F., Gazem, N. (eds) Emerging Trends in Intelligent Computing and Informatics. IRICT 2019. Advances in Intelligent Systems and Computing, vol 1073. Springer, Cham. https://doi.org/10.1007/978-3-030-33582-3_17
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DOI: https://doi.org/10.1007/978-3-030-33582-3_17
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