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An Integrated Approach for Modeling Ontology-Based Task Knowledge on an Incident Command System

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  • Kwoting Fang

    (National Yunlin University of Science and Technology, Douliu City, Yunlin County 640, Taiwan)

  • Shuoche Lin

    (National Yunlin University of Science and Technology, Douliu City, Yunlin County 640, Taiwan)

Abstract

This paper presents the TTIPP methodology, an integration of task analysis, task ontology, integration definition function modeling (IDEF0), Petri net, and Petri net mark language (PNML), to organize and model the task knowledge in the form of natural language expressions acquired during the knowledge-acquisition process. The goal of the methodology is to make the tasks more useful, accessible, and sharable through the web for a variety of stakeholders interested in solving a problem which is expressed mostly in linguistic form, and to shed light on the nature of problem-solving knowledge. This study provides a core epistemology for the knowledge engineer while developing the task ontology for a generic task. The proposed model overcomes the drawbacks of IDEF0, which are its static nature and Petri net which has no concept of hierarchy. A good number of countries lie on the typhoon and earthquake belts, which make them vulnerable to natural calamities. However, a practical incident command system (ICS) that provides a common framework to allow emergency responders of different backgrounds to work together effectively for standardized, on-the-scene, incident management has yet to be developed. There is a strong need to explicitly share, copy, and reuse the existing problem-solving knowledge in a complex ICS. As an example, the TTIPP model is applied to the task of emergency response for debris-flow during a typhoon as a part of an ICS.

Suggested Citation

  • Kwoting Fang & Shuoche Lin, 2019. "An Integrated Approach for Modeling Ontology-Based Task Knowledge on an Incident Command System," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:12:p:3484-:d:242759
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    References listed on IDEAS

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    1. Mohammad Nazir Ahmad & Nor Hidayati Zakaria & Darshana Sedera, 2011. "Ontology-Based Knowledge Management for Enterprise Systems," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 7(4), pages 64-90, October.
    2. Joe Miemczyk & Thomas Johnsen & Monica Macquet, 2012. "Sustainable purchasing and supply management: a structured literature review of definitions and measures at the dyad, chain and network levels," Post-Print hal-00858680, HAL.
    3. Xiaoliang Meng & Chao Xu & Xinxia Liu & Junming Bai & Wenhan Zheng & Hao Chang & Zhuo Chen, 2018. "An Ontology-Underpinned Emergency Response System for Water Pollution Accidents," Sustainability, MDPI, vol. 10(2), pages 1-18, February.
    4. H. Sofia Pinto & C. Tempich & Steffen Staab, 2009. "Ontology Engineering and Evolution in a Distributed World Using DILIGENT," International Handbooks on Information Systems, in: Steffen Staab & Rudi Studer (ed.), Handbook on Ontologies, pages 153-176, Springer.
    5. Agnieszka Konys, 2018. "An Ontology-Based Knowledge Modelling for a Sustainability Assessment Domain," Sustainability, MDPI, vol. 10(2), pages 1-27, January.
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    Cited by:

    1. Peng Ye & Xueying Zhang & Ge Shi & Shuhui Chen & Zhiwen Huang & Wei Tang, 2020. "TKRM: A Formal Knowledge Representation Method for Typhoon Events," Sustainability, MDPI, vol. 12(5), pages 1-19, March.

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