[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 :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
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
External co-authors :
yes
Language :
English
Title :
A Methodological Framework to Design a Machine-Readable Privacy Icon Set
Publication date :
2018
Event name :
21st International Legal Informatics Symposium IRIS 2018
Event place :
Salzburg, Austria
Event date :
from 21-02-2018 to 23-02-2018
Audience :
International
Main work title :
Data Protection / LegalTech Proceedings of the 21st International Legal Informatics Symposium IRIS 2018
Editor :
Schweighofer, Erich
Peer reviewed :
Peer reviewed
Focus Area :
Law / European Law Security, Reliability and Trust
Name of the research project :
R-AGR-0026 - LAST-JD - part UL (20130901-20201231) - VAN DER TORRE Leon
