Jusletter IT

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

  • Authors: Monica Palmirani / Arianna Rossi / Michele Martoni / Margaret Hagan
  • Category: Articles
  • Region: Italy, USA
  • Field of law: Legal Visualisation
  • Collection: Conference proceedings IRIS 2018
  • Citation: Monica Palmirani / Arianna Rossi / Michele Martoni / Margaret Hagan, A Methodological Framework to Design a Machine-readable Privacy Icon Set, in: Jusletter IT 22 February 2018
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.

Table of contents

  • 1. Introduction
  • 2. Project Overview: Machine-Readable, Standardized, Visual Elements for Privacy Policies
  • 3. Methodology
  • 3.1. Analysis of Legal Requirements
  • 3.2. Formalization of Legal Knowledge
  • 3.3. Participatory, Human-Centered Design to Convert Formal Knowledge into Visuals
  • 3.4. Empirical Evaluation
  • 4. Limitations and Conclusions
  • 5. References

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