Understanding and improving business processes have become important success factors for organizations. Process mining has proven very successful with a variety of methods and techniques, including discovering process models based on event logs. Process mining has traditionally focussed on control flow and timing aspects. However, getting insights about a process is not only based on activities and their orderings, but also on the data generated and manipulated during process executions. Today, almost every process activity generates data; these data do not play the role in process mining that it deserves. This paper introduces a visualization technique for enhancing discovered process models with domain data, thereby allowing data-based exploration of processes. Data-enhanced process models aim at supporting domain experts to explore the process, where they can select attributes of interest and observe their influence on the process. The visualization technique is illustrated by the MIMIC-IV real-world data set on hospitalizations in the US.

中文翻译：

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流程挖掘中的数据增强流程模型

了解和改进业务流程已成为组织的重要成功因素。流程挖掘已证明使用各种方法和技术非常成功，包括基于事件日志发现流程模型。流程挖掘传统上侧重于控制流和时序方面。然而，了解流程不仅基于活动及其顺序，还基于流程执行期间生成和操作的数据。今天，几乎每个流程活动都会生成数据；这些数据在过程挖掘中没有发挥应有的作用。本文介绍了一种可视化技术，用于使用领域数据增强已发现的流程模型，从而允许对流程进行基于数据的探索。数据增强的流程模型旨在支持领域专家探索流程，他们可以选择感兴趣的属性并观察它们对过程的影响。MIMIC-IV 真实世界的美国住院数据集说明了可视化技术。