This paper introduces PrOnto, a legal ontology of the GDPR1 with the goal of providing a legal knowledge modelling of its conceptual cores: privacy agents, data types, types of processing operations, rights and obligations. This recently introduced Regulation places upon entities that process personal data the obligation of assessing the risks they could encounter and of adapting their duties on the basis of the impact assessment , including specific measures that intend to safeguard the data subject's human dignity and fundamental rights. In this paper, we argue and show how legal compliance and privacy-by-design can be supported and eased by Semantic web technologies and legal reasoning tools. A specific focus is placed on the Risk Analysis ontological module: we intend to demonstrate that PrOnto is capable of supporting compliance checking between risks and measures. The methodology used here is based on legal theory analysis joined with ontological patterns.

PrOnto: Privacy Ontology for Legal Compliance

Monica Palmirani
Writing – Original Draft Preparation
;
Michele Martoni
Writing – Original Draft Preparation
;
Arianna Rossi
Writing – Original Draft Preparation
;
2018

Abstract

This paper introduces PrOnto, a legal ontology of the GDPR1 with the goal of providing a legal knowledge modelling of its conceptual cores: privacy agents, data types, types of processing operations, rights and obligations. This recently introduced Regulation places upon entities that process personal data the obligation of assessing the risks they could encounter and of adapting their duties on the basis of the impact assessment , including specific measures that intend to safeguard the data subject's human dignity and fundamental rights. In this paper, we argue and show how legal compliance and privacy-by-design can be supported and eased by Semantic web technologies and legal reasoning tools. A specific focus is placed on the Risk Analysis ontological module: we intend to demonstrate that PrOnto is capable of supporting compliance checking between risks and measures. The methodology used here is based on legal theory analysis joined with ontological patterns.
Proceedings of the 18th European Conference on Digital Government ECDG 2018
142
151
Monica Palmirani, Michele Martoni, Arianna Rossi, Cesare Bartolini, Livio Robaldo
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/648220
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