Process cubes: slicing, dicing, rolling up and drilling down event data for process mining

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Recent breakthroughs in process mining research make it possible to discover, analyze, and improve business processes based on event data. The growth of event data provides many opportunities but also imposes new challenges. Process mining is typically done for an isolated well-defined process in steady-state. However, the boundaries of a process may be fluid and there is a need to continuously view event data from different angles. This paper proposes the notion of process cubes where events and process models are organized using different dimensions. Each cell in the process cube corresponds to a set of events and can be used to discover a process model, to check conformance with respect to some process model, or to discover bottlenecks. The idea is related to the well-known OLAP (Online Analytical Processing) data cubes and associated operations such as slice, dice, roll-up, and drill-down. However, there are also significant differences because of the process-related nature of event data. For example, process discovery based on events is incomparable to computing the average or sum over a set of numerical values. Moreover, dimensions related to process instances (e.g. cases are split into gold and silver customers), subprocesses (e.g. acquisition versus delivery), organizational entities (e.g. backoffice versus frontoffice), and time (e.g., 2010, 2011, 2012, and 2013) are semantically different and it is challenging to slice, dice, roll-up, and drill-down process mining results efficiently.

Original languageEnglish
Title of host publicationAsia Pacific Business Process Management
Subtitle of host publicationFirst Asia Pacific Conference, AP-BPM 2013 Beijing, China, August 29-30, 2013 Selected Papers
EditorsM. Song, M.T. Wynn, J. Liu
Place of PublicationDordrecht
Number of pages22
ISBN (Electronic)978-3-319-02922-1
ISBN (Print)978-3-319-02921-4
Publication statusPublished - 2017
Event1st Asia Pacific Conference on Business Process Management (AP-BPM 2013) - Beijing, China
Duration: 29 Aug 201330 Aug 2013
Conference number: 1

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)1865-1348


Conference1st Asia Pacific Conference on Business Process Management (AP-BPM 2013)
Abbreviated titleAP-BPM 2013


  • Big Data
  • Conformance Checking
  • OLAP
  • Process Discovery
  • Process Mining


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