The analysis of fairness in process mining is a significant aspect of data-driven decision-making, yet the advancement in this field is constrained due to the scarcity of event data that incorporates fairness considerations. To bridge this gap, we present a collection of simulated event logs, spanning four critical domains, which encapsulate a variety of discrimination scenarios. By simulating these event logs with CPN Tools, we ensure data with known ground truth, thereby offering a robust foundation for fairness analysis. These logs are made freely available under the CC-BY-4.0 license and adhere to the XES standard, thereby assuring broad compatibility with various process mining tools. This initiative aims to empower researchers with the requisite resources to test and develop fairness techniques within process mining, ultimately contributing to the pursuit of equitable, data-driven decision-making processes.

翻译：流程挖掘中的公平性分析是数据驱动决策的重要方面，但由于缺乏包含公平性考量的事件数据，该领域的发展受到制约。为弥合这一差距，我们提出了一组涵盖四个关键领域的模拟事件日志，这些日志封装了多种歧视场景。通过使用CPN工具模拟这些事件日志，我们确保数据具有已知的真实情况，从而为公平性分析提供坚实基础。这些日志根据CC-BY-4.0许可证免费提供，并遵循XES标准，从而确保与各种流程挖掘工具广泛兼容。该举措旨在为研究人员提供必要资源，以测试和开发流程挖掘中的公平性技术，最终促进追求公平、数据驱动的决策过程。