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Process Mining Reloaded: Event Structures as a Unified Representation of Process Models and Event Logs

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Application and Theory of Petri Nets and Concurrency (PETRI NETS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9115))

Abstract

Process mining is a family of methods to analyze event logs produced during the execution of business processes in order to extract insights regarding their performance and conformance with respect to normative or expected behavior. The landscape of process mining methods and use cases has expanded considerably in the past decade. However, the field has evolved in a rather ad hoc manner without a unifying foundational theory that would allow algorithms and theoretical results developed for one process mining problem to be reused when addressing other related problems. In this paper we advocate a foundational approach to process mining based on a well-known model of concurrency, namely event structures. We outline how event structures can serve as a unified representation of behavior captured in process models and behavior captured in event logs. We then sketch how process mining operations, specifically automated process discovery, conformance checking and deviance mining, can be recast as operations on event structures.

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Authors and Affiliations

  1. University of Tartu, Tartu, Estonia

    Marlon Dumas & Luciano García-Bañuelos

Authors
  1. Marlon Dumas
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  2. Luciano García-Bañuelos
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Correspondence to Marlon Dumas .

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Editors and Affiliations

  1. Université Libre de Bruxelles, Brussels, Belgium

    Raymond Devillers

  2. Tampere University of Technology, Tampere, Finland

    Antti Valmari

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Dumas, M., García-Bañuelos, L. (2015). Process Mining Reloaded: Event Structures as a Unified Representation of Process Models and Event Logs. In: Devillers, R., Valmari, A. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2015. Lecture Notes in Computer Science(), vol 9115. Springer, Cham. https://doi.org/10.1007/978-3-319-19488-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-19488-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19487-5

  • Online ISBN: 978-3-319-19488-2

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