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Turning Logs into Lumber: Preprocessing Tasks in Process Mining

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Process Mining Workshops (ICPM 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 503))

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Abstract

Event logs are invaluable for conducting process mining projects, offering insights into process improvement and data-driven decision-making. However, data quality issues affect the correctness and trustworthiness of these insights, making preprocessing tasks a necessity. Despite the recognized importance, the execution of preprocessing tasks remains ad-hoc, lacking support. This paper presents a systematic literature review that establishes a comprehensive repository of preprocessing tasks and their usage in case studies. We identify six high-level and 20 low-level preprocessing tasks in case studies. Log filtering, transformation, and abstraction are commonly used, while log enriching, integration, and reduction are less frequent. These results can be considered a first step in contributing to more structured, transparent event log preprocessing, enhancing process mining reliability.

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Authors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Ying Liu, Vinicius Stein Dani, Iris Beerepoot & **xi Lu

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  1. Ying Liu
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  2. Vinicius Stein Dani
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  3. Iris Beerepoot
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  4. **xi Lu
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Correspondence to **xi Lu .

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Editors and Affiliations

  1. KU Leuven, Leuven, Belgium

    Johannes De Smedt

  2. University of Haifa, Haifa, Israel

    Pnina Soffer

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Liu, Y., Stein Dani, V., Beerepoot, I., Lu, X. (2024). Turning Logs into Lumber: Preprocessing Tasks in Process Mining. In: De Smedt, J., Soffer, P. (eds) Process Mining Workshops. ICPM 2023. Lecture Notes in Business Information Processing, vol 503. Springer, Cham. https://doi.org/10.1007/978-3-031-56107-8_8

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  • DOI: https://doi.org/10.1007/978-3-031-56107-8_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56106-1

  • Online ISBN: 978-3-031-56107-8

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