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Experts such as the National Consortium for the Study of Terrorism and Responses to Terrorism (START) collect data about terrorism and publish it in the Global Terrorism Database (GTD). Thus, the data is deficient in the technical modeling of its metadata. In this paper, we proposed GTD Ontology (GTDOnto) to organize the knowledge about terrorism and model the terrorist incidents, targets, attackers, weapons, and other related information. Based on the NeOn methodology, the goal is to build on the effort of START and present controlled vocabularies in a machine-readable format that is interoperable and can be reused to describe potential incidents in the future. The GTDOnto was implemented with the Web Ontology Language (OWL) using Protégé editor and evaluated by answering competency questions, domain experts' opinions, and running examples of GTDOnto for representing actual incidents.

创建时间:
2022-08-30
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