Patterns for legal compliance checking in a decidable framework of linked open data

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Francesconi, Enrico
Governatori, Guido
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2022
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Abstract

This paper presents an approach for legal compliance checking in the Semantic Web which can be effectively applied for applications in the Linked Open Data environment. It is based on modeling deontic norms in terms of ontology classes and ontology property restrictions. It is also shown how this approach can handle norm defeasibility. Such methodology is implemented by decidable fragments of OWL 2, while legal reasoning is carried out by available decidable reasoners. The approach is generalised by presenting patterns for modeling deontic norms and norms compliance checking.

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Artificial Intelligence and Law

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© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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Artificial intelligence

Law and legal studies

Science & Technology

Social Sciences

Technology

Computer Science, Artificial Intelligence

Computer Science, Interdisciplinary Applications

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Francesconi, E; Governatori, G, Patterns for legal compliance checking in a decidable framework of linked open data, Artificial Intelligence and Law, 2022

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