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Space-Time Cube Operations in Process Mining

Abstract : Process mining techniques provide data-driven visualizations that help gaining multi-perspective insights into business processes. These techniques build on a variety of algorithms, however without any explicit reference to the spectrum of potential analysis of operations. For this reason, it is unclear if the state of the art of process mining has missed opportunities to develop techniques that could be of potential value to an analyst. In this paper, we refer to research on information visualization where this problem has been addressed from a more general angle. More specifically, we use the framework defined for space-time cube operations to explore to which extent process mining instantiates these operations. To this end, we refer to most widely used commercial process mining tools and analyze their analysis operations. We find that the majority of the operations are already supported by the tools, but there are still unsupported ones, which exhibit opportunities for future research and tool innovation.
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https://hal.inria.fr/hal-03434663
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Submitted on : Thursday, November 18, 2021 - 1:39:30 PM
Last modification on : Friday, November 19, 2021 - 4:51:37 PM
Long-term archiving on: : Saturday, February 19, 2022 - 7:05:17 PM

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Dina Bayomie, Lukas Pfahlsberger, Kate Revoredo, Jan Mendling. Space-Time Cube Operations in Process Mining. 13th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling (PoEM 2020), Nov 2020, Riga, Latvia. pp.405-414, ⟨10.1007/978-3-030-63479-7_28⟩. ⟨hal-03434663⟩

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