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Trust and Privacy in Process Analytics

dc.contributor.authorMannhardt, Felix
dc.contributor.authorKoschmider, Agnes
dc.contributor.authorBiermann, Lars
dc.contributor.authorLange, Jana
dc.contributor.authorTschorsch, Florian
dc.contributor.authorWynn, Moe Thandar
dc.date.accessioned2023-05-11T05:44:29Z
dc.date.available2023-05-11T05:44:29Z
dc.date.issued2020
dc.description.abstractThis paper summarizes the panel discussion at the 1st Workshop on Trust and Privacy in Process Analytics (TPPA) co-located with the 2nd International Conference on Process Mining. The panel discussed to what extend trust and privacy is embedded in applications of process mining and took place on 5th October 2020. The virtual session was chaired by Felix Mannhardt and Agnes Koschmider and the invited panelists were Moe Wynn, Jana Lange, Lars Biermann and Florian Tschorsch. The major challenges that this panel identified related to privacy-preserving process mining are to include (user-centric) privacy filters, understanding the privacy-utility trade-off and to link privacy-preserving techniques with dataset quality.en
dc.identifier.doi10.18417/emisa.15.8
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/41488
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofEnterprise Modelling and Information Systems Architectures (EMISAJ) – International Journal of Conceptual Modeling: Vol. 15, Nr. 8
dc.subjectprivacy process mining
dc.titleTrust and Privacy in Process Analyticsen
dc.typeText/Journal Article
gi.citation.endPage4
gi.citation.publisherPlaceBerlin
gi.citation.startPage1

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