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Disaster Management Knowledge Analysis Framework Validated

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Abstract

In Disaster Management (DM), reusing knowledge of best practices from past experiences is envisaged as the best approach for dealing with future disasters. But analysing and modelling processes involved in those experiences is a well-known challenge. But the efficient storage of those processes to allow reuse by others in future DM endeavours is even more challenging and less discussed. Without an efficient process in place, DM knowledge reuse becomes even more remote as the effort incurred gets construed as a hindrance to more pressing activities during the execution of disaster activities. Efficiency has to also be pursued without compromising the effectiveness of the knowledge analysis and reuse. It is important to ensure that knowledge remains meaningful and relevant after it is transformed. This paper presents and validates a DM knowledge analysis framework (DMKAF 2.0) that caters for efficient transformation of DM knowledge intended for reuse. The paper demonstrates that undertaking knowledge transformation and storage in the context of its use is crucial in DM for both, effectiveness and efficiency of the transformation process. Design Science Research methodology guides the research undertaken, by informing enhancements and how the framework is evaluated. A real case study of flood DM from the State Emergency Service of Victoria State Australia is successfully used to validate these enhancements.

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Acknowledgements

The authors would like to thank Mr. Andrew Sheehan and Mr. Simon Opper, as the DM experts from the SES Victoria and New South Wales States of Australia respectively for their contributions to the evaluation of the research. Their involvements and feedbacks in the evaluation activities has helped the authors with the improved version of the framework.

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Authors and Affiliations

  1. Department of Informatics Engineering, Universitas Papua, Manokwari, Indonesia

    Dedi I. Inan

  2. Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, Sydney, Australia

    Ghassan Beydoun & Biswajeet Pradhan

  3. Department of Energy and Mineral Resources Engineering, Sejong University, Choongmu-gwan, 209 Neungdong-ro, Gwangjin-gu, Seoul, 05006, Korea

    Biswajeet Pradhan

  4. Center of Excellence for Climate Change Research, King Abdulaziz University, P. O. Box 80234, Jeddah, 21589, Saudi Arabia

    Biswajeet Pradhan

  5. Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Selangor, Malaysia

    Biswajeet Pradhan

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  1. Dedi I. Inan
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Correspondence to Dedi I. Inan.

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Appendix 1

Appendix 1

Table 5 Evaluation outcome of benefits and usability of the deposited knowledge from the DM experts of the SES State of Victoria and New South Wales of Australia
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Inan, D.I., Beydoun, G. & Pradhan, B. Disaster Management Knowledge Analysis Framework Validated. Inf Syst Front 24, 2077–2097 (2022). https://doi.org/10.1007/s10796-022-10245-w

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