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Agent-Based Knowledge Analysis Framework in Disaster Management

Author

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  • Dedi Iskandar Inan

    (Universitas Negeri Papua
    University of Technology Sydney)

  • Ghassan Beydoun

    (University of Technology Sydney)

  • Simon Opper

    (State Emergency Service New South Wales)

Abstract

Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge-intensive and time sensitive. Timely sharing of the required knowledge is critical for DM. For recurring disasters (e.g. floods), developed countries tend to have dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner, and sharing activities between plans, often requires significant domain knowledge and intimate understanding of the plans in the first place. This paper introduces an Agent-Based (AB) knowledge analysis method to convert DISPLANs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching of knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood DISPLANs plans used by SES (State Emergency Service), an authoritative DM agency in New South Wales (NSW) State of Australia (hereinafter referred to as SES NSW) to illustrate and give a preliminary validation of the approach. It is illustrated by using displans along the flood-prone Murrumbidgee river in central NSW.

Suggested Citation

  • Dedi Iskandar Inan & Ghassan Beydoun & Simon Opper, 2018. "Agent-Based Knowledge Analysis Framework in Disaster Management," Information Systems Frontiers, Springer, vol. 20(4), pages 783-802, August.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:4:d:10.1007_s10796-017-9792-9
    DOI: 10.1007/s10796-017-9792-9
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    References listed on IDEAS

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    1. Susanne Becken & Roché Mahon & Hamish Rennie & Aishath Shakeela, 2014. "The tourism disaster vulnerability framework: an application to tourism in small island destinations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(1), pages 955-972, March.
    2. R. B. K. Brown & G. Beydoun & G. Low & W. Tibben & R. Zamani & F. García-Sánchez & R. Martinez-Bejar, 2016. "Computationally efficient ontology selection in software requirement planning," Information Systems Frontiers, Springer, vol. 18(2), pages 349-358, April.
    3. Wex, Felix & Schryen, Guido & Feuerriegel, Stefan & Neumann, Dirk, 2014. "Emergency response in natural disaster management: Allocation and scheduling of rescue units," European Journal of Operational Research, Elsevier, vol. 235(3), pages 697-708.
    4. Marijn Janssen & JinKyu Lee & Nitesh Bharosa & Anthony Cresswell, 2010. "Advances in multi-agency disaster management: Key elements in disaster research," Information Systems Frontiers, Springer, vol. 12(1), pages 1-7, March.
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    Cited by:

    1. Dedi I. Inan & Ghassan Beydoun & Siti Hajar Othman, 2023. "Risk Assessment and Sustainable Disaster Management," Sustainability, MDPI, vol. 15(6), pages 1-5, March.
    2. Ghassan Beydoun & Sergiu Dascalu & Dale Dominey-Howes & Andrew Sheehan, 2018. "Disaster Management and Information Systems: Insights to Emerging Challenges," Information Systems Frontiers, Springer, vol. 20(4), pages 649-652, August.
    3. Dedi I. Inan & Ghassan Beydoun & Biswajeet Pradhan, 2022. "Disaster Management Knowledge Analysis Framework Validated," Information Systems Frontiers, Springer, vol. 24(6), pages 2077-2097, December.
    4. Dedi I. Inan & Ghassan Beydoun & Siti Hajar Othman & Biswajeet Pradhan & Simon Opper, 2022. "Developing Reusable COVID-19 Disaster Management Plans Using Agent-Based Analysis," Sustainability, MDPI, vol. 14(12), pages 1-22, June.

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