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arXiv · 2309.17100

Turning Logs into Lumber: Preprocessing Tasks in Process Mining

Ying Liu·Vinicius Stein Dani·Iris Beerepoot·Xixi Lu
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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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Ying Liu, Vinicius Stein Dani, Iris Beerepoot, Xixi Lu. 2023-09-29. Turning Logs into Lumber: Preprocessing Tasks in Process Mining. https://arxiv.org/abs/2309.17100

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