From Declarative Knowledge to Process-based Crisis Resolution: application to Flood Management

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2019-01-08

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Crisis resolution is often based on official government plans that provide guidelines. In real time, when a crisis occurs, one or several plans have to be chosen, merged, refined to meet the specific requirements of the crisis, and then launched. Plans are often in a textual format, which makes their interpretation ambiguous and error prone. Therefore, in real time, the coordination of stakeholders becomes difficult and time consuming. Given these drawbacks, the transformation of a plan into a process provides several advantages: i) an accurate and machine-readable specification of coordination of actions to be done in the field, ii) a better common understanding between stakeholders responsible for these actions and iii) a mean to analyze, simulate and evaluate the crisis response before launching it. The problem being addressed in this paper is “how to deduce a process for driving crisis resolution from business knowledge (plans, stakeholders and their capacities) and relevant facts observed in the impacted field”. This paper presents first a meta-model for capturing business knowledge and crisis situation and then a deduction approach deriving a process in a BPMN-like format. Flood of the Loire in June 2016 serves as a support for approach experiment.

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Disaster Information, Technology, and Resilience in Digital Government, Digital Government, Crisis Management, Flood , Process Deduction, Process Mining

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10 pages

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Proceedings of the 52nd Hawaii International Conference on System Sciences

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Attribution-NonCommercial-NoDerivatives 4.0 International

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