| Reference : An Agile Approach to Validate a Formal Representation of the GDPR |
| Scientific journals : Article | |||
| Law, criminology & political science : Multidisciplinary, general & others Engineering, computing & technology : Computer science | |||
| Security, Reliability and Trust | |||
| http://hdl.handle.net/10993/39327 | |||
| An Agile Approach to Validate a Formal Representation of the GDPR | |
| English | |
| Bartolini, Cesare [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
Lenzini, Gabriele  [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
| Santos, Cristiana [> >] | |
| 2019 | |
| JSAI International Symposium on Artificial Intelligence | |
| Springer Nature | |
| 11717 | |
| Lecture Notes in Artificial Intelligence (LNAI) | |
| Yes | |
| International | |
| 978-3-030-31604-4 | |
| Switzerland | |
| [en] GDPR ; Data Protection Compliance ; Legal Validation ; Usability | |
| [en] Modeling in a knowledge base of logic formulæ the articles of the GDPR enables 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
<br />AQ2 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 AQ3 model of the GDPR, called DAPRECO knowledge base. | |
| Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Applied Security and Information Assurance Group (APSIA) | |
| Fonds National de la Recherche - FnR | |
| DAPRECO (Data Protection Compliance) | |
| Researchers ; Students ; Professionals | |
| http://hdl.handle.net/10993/39327 | |
| also: http://hdl.handle.net/10993/40576 | |
| https://doi.org/10.1007/978-3-030-31605-1_13 | |
| The original publication is available at www.springerlink.com | |
| FnR ; FNR11333956 > Gabriele Lenzini > DAPRECO > DAta Protection REgulation COmpliance > 01/02/2017 > 30/06/2019 > 2016 |
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