The Identification and Creation of Ontologies for the Use in Law Enforcement AI Solutions – MAGNETO Platform Use Case

Kozik, Rafał; Choraś, Michał; Pawlicki, Marek; Hołubowicz, Witold; Pallmer, Dirk; Mueller, Wilmuth; Behmer, Ernst-Josef; Loumiotis, Ioannis; Demestichas, Konstantinos; Horincar, Roxana; Laudy, Claire; Faure, David

doi:10.1007/978-3-030-28374-2_29

Cited by 2 publications

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“…The preceding paper is an extension of our previous work 27 and aimed to delineate the importance of creating an ontology to provide the semantic context to both the AI and the multitude of entities operating on similar data in the domain of law enforcement. The process of developing a common representational model growing out of several preexisting ontologies, bridging the gaps between them, and building on top of them has been emphasized.…”

Section: Discussionmentioning

confidence: 99%

Common Representational Model and Ontologies for Effective Law Enforcement Solutions

Kozik

Choraś

Pawlicki

et al. 2020

Vietnam J. Comp. Sci.

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Ontologies have developed into a prevailing technique for establishing semantic interoperability among heterogeneous systems transacting information. An ontology is an unambiguous blueprint of a concept. For Artificial Intelligence, only the defined notions can be considered existent. Thus, in relation to AI, an ontology can be understood as part of a program which delineates a collection of descriptions. An ontology, therefore, correlates the labels of the entities in the universe of discourse with wording that holds meaning for humans, explaining what those labels signify, along with the precise principles that force the interpretation and semantic utilization of these labels. An ontology constitutes a proper statement of a logical theory. It is a crucial component of a system with the capability to process, manage, analyze, correlate and reason from the large datasets characterized by heterogeneity. This paper depicts the process of development of a Common Representational Model (CRM) on top of several ontologies, taxonomies and classifications to facilitate computational and data mining functionalities. The building blocks of said CRM are delineated in detail, as well as its application in a specific use case.

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Section: Discussionmentioning

confidence: 99%