[en] The GDPR suggests icons to convey data practices in a more straightforward way. Although vi- sualizations to represent legal terms have many benefits, there is fear that they could be misrep- resented by designers and misinterpreted by individuals, thus hindering instead of facilitating the comprehension. In order to solve these issues, we present a methodology to generate legal visual representations that is based on an analysis of legal requirements, on an ontological representation of the legal knowledge, and on an iterative, multi-stakeholder design approach, followed by empirical evaluation.
Disciplines :
Ingénierie, informatique & technologie: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
Palmirani, Monica; University of Bologna > CIRSFID
ROSSI, Arianna ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) ; University of Bologna > CIRSFID
Martoni, Michele; University of Bologna > CIRSFID
Margaret, Hagan; Stanford University > Stanford Law's Center on the Legal Profession
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A Methodological Framework to Design a Machine-Readable Privacy Icon Set
Date de publication/diffusion :
2018
Nom de la manifestation :
21st International Legal Informatics Symposium IRIS 2018
Lieu de la manifestation :
Salzburg, Autriche
Date de la manifestation :
from 21-02-2018 to 23-02-2018
Manifestation à portée :
International
Titre de l'ouvrage principal :
Data Protection / LegalTech Proceedings of the 21st International Legal Informatics Symposium IRIS 2018
Editeur scientifique :
Schweighofer, Erich
Peer reviewed :
Peer reviewed
Focus Area :
Law / European Law Security, Reliability and Trust
Intitulé du projet de recherche :
R-AGR-0026 - LAST-JD - part UL (20130901-20201231) - VAN DER TORRE Leon
