Visualising Personal Data Flows: Insights from a Case Study of Booking.com
Abstract
Commercial organisations are holding and processing an ever-increasing amount of personal data. Policies and laws are continually changing to require these companies to be more transparent regarding the collection, storage, processing and sharing of this data. This paper reports our work of taking Booking.com as a case study to visualise personal data flows extracted from their privacy policy. By showcasing how the company shares its consumers' personal data, we raise questions and extend discussions on the challenges and limitations of using privacy policies to inform online users about the true scale and the landscape of personal data flows. This case study can inform us about future research on more data flow-oriented privacy policy analysis and on the construction of a more comprehensive ontology on personal data flows in complicated business ecosystems.
Cite
@article{arxiv.2304.09603,
title = {Visualising Personal Data Flows: Insights from a Case Study of Booking.com},
author = {Haiyue Yuan and Matthew Boakes and Xiao Ma and Dongmei Cao and Shujun Li},
journal= {arXiv preprint arXiv:2304.09603},
year = {2024}
}
Comments
This is the full edition of a paper published in Intelligent Information Systems: CAiSE Forum 2023, Zaragoza, Spain, June 12-16, 2023, Proceedings, Lecture Notes in Business Information Processing (LNBIP), Volume 477, pp. 52-60, 2023, Springer Nature, https://link.springer.com/book/10.1007/978-3-031-34674-3_7