Space-Time Cube Operations in Process Mining - The Practice of Enterprise Modeling Access content directly
Conference Papers Year : 2020

Space-Time Cube Operations in Process Mining

Dina Bayomie
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  • PersonId : 1117195
Kate Revoredo
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  • PersonId : 1117197
Jan Mendling
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  • PersonId : 977590

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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hal-03434663 , version 1 (18-11-2021)

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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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