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.
Monica Palmirani, A.R. (2018). A Methodological Framework to Design a Machine-Readable Privacy Icon Set. Bern : Editions Weblaw.
A Methodological Framework to Design a Machine-Readable Privacy Icon Set
Monica Palmirani
;Arianna Rossi
;Michele Martoni
;
2018
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.File | Dimensione | Formato | |
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methodology_ePub.pdf
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Descrizione: A Methodological Framework to Design a Machine-Readable Privacy Icon Set
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Scan_0002 copy - signed MDH copy.pdf
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