Visualising personal data flows: insights from a case study of

Yuan, H., Boakes, M., Ma, X. ORCID: 0000-0003-1318-3590, Cao, D. ORCID: 0000-0002-2614-3726 and Li, S., 2023. Visualising personal data flows: insights from a case study of In: C. Cabanillas and F. Pérez, eds., Intelligent information systems: CAiSE forum 2023, Zaragoza, Spain, June 12–16, 2023, proceedings. Cham: Springer, pp. 52-60. ISBN 9783031346736

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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 collection, storage, processing and sharing of this data. This paper reports our work of taking 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.

Item Type: Chapter in book
Creators: Yuan, H., Boakes, M., Ma, X., Cao, D. and Li, S.
Publisher: Springer
Place of Publication: Cham
Date: 8 June 2023
ISBN: 9783031346736
Rights: Use of this Author Accepted Manuscript is subject to Springer Nature's terms of use:
Divisions: Schools > Nottingham Business School
Record created by: Laura Ward
Date Added: 02 Nov 2023 08:53
Last Modified: 02 Nov 2023 08:53

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