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This report documents the program and the outcomes of Dagstuhl Seminar 25152 "Multi-Faceted Visual Process Mining and Analytics". The seminar brought together experts from the process mining (PM) community and the visual analytics (VA) community to strengthen the identified synergies of both fields and identify further novel and promising research directions. A particular focus of the seminar was on the challenges arising from the multi-faceted nature of processes and the multi-faceted data to be investigated. The relevant facets include time (when do processes happen), space (where do processes happen), topology (how are processes connected), object centricity (how are processes characterized), uncertainty (what are we unsure about), analytic provenance (how did we obtain our knowledge), and more. This report deals with challenges related to these different data facets, individually and in combination. As a general principle, VA methods are advocated to be an integral part of all phases of the PM process to facilitate a comprehensive multi-faceted data exploration, hypothesis generation, and presentation of results. More concretely, the discussions revolve around several aspects at the crossroads of the two disciplines workflows, including the data facets under analysis, the human factors at play, the catalog of aided tasks, novel combinations of visual, interactive, and computational methods, as well as integration, scalability, and general applicability of the devised solutions.
@Article{diciccio_et_al:DagRep.15.4.28,
author = {Di Ciccio, Claudio and Soffer, Pnina and Tominski, Christian and Vrotsou, Katerina and Meroni, Giovanni},
title = {{Multi-Faceted Visual Process Mining and Analytics (Dagstuhl Seminar 25152)}},
pages = {28--78},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2025},
volume = {15},
number = {4},
editor = {Di Ciccio, Claudio and Soffer, Pnina and Tominski, Christian and Vrotsou, Katerina and Meroni, Giovanni},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.4.28},
URN = {urn:nbn:de:0030-drops-252573},
doi = {10.4230/DagRep.15.4.28},
annote = {Keywords: human in the loop, process mining, visual analytics}
}