Abstract
We argue that, with the growth of process mining in breadth (variety of covered tasks) and depth (sophistication of the considered process models), event logs need to be augmented by commonsense knowledge to provide a better input for process mining algorithms. This is crucial to infer key facts that are not explicitly recorded in the logs, but are necessary in a variety of tasks, such as understanding the event data, assessing their compliance and quality, identifying outliers and clusters, computing statistics, and discovering decisions, ultimately empowering process mining as a whole.