Process Mining and Perceived Privacy Violations: A Pilot-Study

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Abstract

Despite the existence of various methods and abstraction techniques to reduce the privacy risk of process models generated by process mining algorithms, it is unclear how process mining stakeholders perceive privacy violations. In this pilot-study various process model visualisations were shown to 6 stakeholders of a travel expense claim process. While changing the abstraction levels of these visualisations, the stakeholders were asked whether they perceived a violation of their privacy. The results show that there are differences in how individual stakeholders perceive privacy violations of process models generated via process mining algorithms. Results differ per type of visualization, type of privacy risk reducing methods, changes of abstraction level and stakeholder role. To reduce the privacy risk, the interviewees suggested to include an authorization table in the process mining tool, communicate the goal of the analysis with all stakeholders, and validate the analysis with a privacy officer. It is suggested that future research focuses on discussing and validating process visualisations and privacy risk reducing methods and techniques with various process mining stakeholders in organisations. This is expected to reduce perceived violations and prevents developing techniques that are aimed at reducing privacy risk but are not considered as such by stakeholders.

Original languageEnglish
Title of host publicationProceedings of the 25th International Conference on Enterprise Information Systems - Volume 2, ICEIS 2023
EditorsJoaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi
PublisherSCITEPRESS
Pages289-296
Number of pages8
ISBN (Electronic)9789897586484
DOIs
Publication statusPublished - 2023
Event25th International Conference on Enterprise Information Systems, ICEIS 2023 - Prague, Czech Republic
Duration: 24 Apr 202326 Apr 2023
Conference number: 25

Publication series

NameInternational Conference on Enterprise Information Systems, ICEIS - Proceedings
Volume2
ISSN (Electronic)2184-4992

Conference

Conference25th International Conference on Enterprise Information Systems, ICEIS 2023
Abbreviated titleICEIS 2023
Country/TerritoryCzech Republic
CityPrague
Period24/04/2326/04/23

Keywords

  • BPM
  • GDPR
  • Perceived privacy
  • Privacy
  • Process mining
  • Process model abstraction

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