# Turning Logs into Lumber: Preprocessing Tasks in Process Mining

arXiv: https://arxiv.org/abs/2309.17100 · HTML: https://mlsanity.com/paper/2309.17100/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Sep 2023.

## Built on by (most cited first, 1 of 1)

- [LLM-based event abstraction and integration for IoT-sourced logs](https://mlsanity.com/paper/2409.03478/) (2024)

## Abstract (arXiv)

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.