The GDPR suggests icons to convey data practices in a more straightforward way. Although visualizations to represent legal terms have many benefits, there is fear that they could be misrepresented 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.

A Methodological Framework to Design a Machine-Readable Privacy Icon Set

Michele Martoni;
2018-01-01

Abstract

The GDPR suggests icons to convey data practices in a more straightforward way. Although visualizations to represent legal terms have many benefits, there is fear that they could be misrepresented 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2691053
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