Abstract

The geographical location of any region, as well as large-scale environmental changes caused by a variety of factors, invite a wide range of disasters. Floods, droughts, earthquakes, cyclones, landslides, tornadoes, and cloudbursts are all common natural disasters that destroy property and kill people. On average, 0.1% of the total deaths globally in the past decade have been due to natural disasters. The National Disaster Management Authority (NDMA), a branch of the Ministry of Home Affairs, plays an important role in disaster management in India by taking responsibility for risk mitigation, response, and recovery from all natural and man-made disasters. This article presents an ontology-based disaster management framework based on the NDMA’s responsibility matrix. This ontological base framework is named as Disaster Management Ontology (DMO). It aids in task distribution among necessary authorities at various stages of a disaster, as well as a knowledge-driven decision support system for financial assistance to victims. In the proposed DMO, ontology has been used to integrate knowledge as well as a working platform for reasoners, and the Decision Support System (DSS) ruleset is written in Semantic Web Rule Language (SWRL), which is based on the First Order Logic (FOL) concept. In addition, OntoGraph, a class view of taxonomy, is used to make taxonomy more interactive for users.

Details

Title
Disaster management ontology- an ontological approach to disaster management automation
Author
Shukla, Deepika 1 ; Azad, Hiteshwar Kumar 2 ; Abhishek, Kumar 1 ; Shitharth, S. 3 

 National Institute of Technology Patna, Computer Science and Engineering, Patna, India (GRID:grid.444650.7) (ISNI:0000 0004 1772 7273) 
 Vellore Institute of Technology Vellore, School of Computer Science and Engineering, Vellore, India (GRID:grid.412813.d) (ISNI:0000 0001 0687 4946) 
 Kebri Dehar University, Department of Computer Science, Kebri Dehar, Ethiopia (GRID:grid.444650.7) 
Pages
8091
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2815861446
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.