Abstract
Modelling in a knowledge base of logic formulæ the articles of the GDPR enables a semi-automatic reasoning of the Regulation. To be legally substantiated, it requires that the formulæ express validly the legal meaning of the Regulation’s articles. But legal experts are usually not familiar with logic, and this calls for an interdisciplinary validation methodology that bridges the communication gap between formal modelers and legal evaluators. We devise such a validation methodology and exemplify it over a knowledge base of articles of the GDPR translated into Reified I/O (RIO) logic and encoded in LegalRuleML. A pivotal element of the methodology is a human-readable intermediate representation of the logic formulæ that preserves the formulæ’s meaning, while rendering it in a readable way to non-experts. After being applied over a use case, we prove that it is possible to retrieve feedback from legal experts about the formal representation of Art. 5.1a and Art. 7.1. What emerges is an agile process to build logic knowledge bases of legal texts, and to support their public trust, which we intend to use for a logic model of the GDPR, called DAPRECO knowledge base.
Bartolini and Lenzini are supported by the FNR CORE project C16/IS/11333956 “DAPRECO: DAta Protection REgulation COmpliance”.
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Notes
- 1.
The name DAPRECO comes from DAta PRotection REgulation COmpliance, the name of the CORE-FNR project that supported this research.
- 2.
- 3.
- 4.
The formulæ are available at https://github.com/dapreco/daprecokb.
- 5.
- 6.
Available at https://github.com/guerret/lu.uni.dapreco.parser.git.
- 7.
The full translations for Articles 5.1 and 7.1 can be found in the repository from note 6, in the “jurisin” folder.
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Bartolini, C., Lenzini, G., Santos, C. (2019). An Agile Approach to Validate a Formal Representation of the GDPR. In: Kojima, K., Sakamoto, M., Mineshima, K., Satoh, K. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2018. Lecture Notes in Computer Science(), vol 11717. Springer, Cham. https://doi.org/10.1007/978-3-030-31605-1_13
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