An Ontology and a Reasoning Approach for Evacuation in Flood Disaster Response

Julie Bu Daher (), Tom Huygue, Patricia Stolf () and Nathalie Hernandez ()
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Julie Bu Daher: IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3, Toulouse, France
Tom Huygue: IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3, Toulouse, France
Patricia Stolf: IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3, UT2, Toulouse, France
Nathalie Hernandez: IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3, UT2, Toulouse, France

Journal of Information & Knowledge Management (JIKM), 2023, vol. 22, issue 06, 1-20

Abstract: Managing flood-related data to assist in the disaster management is a critical process of high importance during a flood disaster. These data are heterogeneous and can be provided from different data sources, and integrating them is a challenging task which allows inferring new information that helps in limiting the consequences of a flood. In this paper, we propose a novel approach that manages heterogeneous flood-related data based on semantic web techniques and helps in limiting the damage caused by floods. We first propose an ontology that is used to formally describe the flood-related data, and we construct our knowledge graph through integrating heterogeneous data using the proposed ontology. Then, we propose a reasoning approach using SHACL rules to infer new information that helps manage the flood disaster or anticipate future events. The experimental evaluations of our proposed approach are conducted on a real case study in flood disaster management with the aim of generating evacuation priorities. The results show that the proposed approach succeeds in managing heterogeneous flood-related data and in generating evacuation priorities in a very short time.

Keywords: Flood disaster management; semantic web; flood ontology; reasoning; SHACL rules (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0219649223500429

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