Communicating processing purposes during personal data collection in web forms is dictated by the GDPR Purpose Limitation principle (Art. 5-1b). Such explanations should be clear, concise, and free of unnecessary jargon to improve user comprehension and decision-making. This work explores the problem of GDPR-compliant transparency in combination with usability as indicated by the usable privacy heuristics and the GDPR, in personal data collecting web forms, and proposes a practical, research-driven solution: a browser-based purposes annotation tool. The study presents the detailed data collection and analysis from 100 real-world websites, the subsequent user-centered design process for prototyping and evaluating transparent form designs resulting in two preferred annotation styles incorporated into the tool, the methodology of creating and validating a dataset of processing purposes for 20 popular fields, and the development of the tool. The final tool was evaluated using the User Experience Questionnaire (UEQ), with positive results.

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Making Data Collection Transparent and Usable: Annotating Web Forms with Processing Purposes

  • Evangelia Vanezi,
  • Anna Vasileiou,
  • George Angelos Papadopoulos

摘要

Communicating processing purposes during personal data collection in web forms is dictated by the GDPR Purpose Limitation principle (Art. 5-1b). Such explanations should be clear, concise, and free of unnecessary jargon to improve user comprehension and decision-making. This work explores the problem of GDPR-compliant transparency in combination with usability as indicated by the usable privacy heuristics and the GDPR, in personal data collecting web forms, and proposes a practical, research-driven solution: a browser-based purposes annotation tool. The study presents the detailed data collection and analysis from 100 real-world websites, the subsequent user-centered design process for prototyping and evaluating transparent form designs resulting in two preferred annotation styles incorporated into the tool, the methodology of creating and validating a dataset of processing purposes for 20 popular fields, and the development of the tool. The final tool was evaluated using the User Experience Questionnaire (UEQ), with positive results.