With the increasing amounts of data we see a rise in data uncertainty, due to varying sources and quality issues. In order to analyze and reason over data within the context of uncertainty, this uncertainty needs to be captured in data models, e.g. by means of probabilistic terms. Therefore process mining needs to consider uncertainty when analyzing logs and data likelihood when learning process models. Analyses, predictions and recommendations should be enriched with stochastic perspective.
In this workshop we aim at bringing together researchers that are interested in stochastic process mining. We are interested in identifying the basic challenges which probabilistic process data brings along and seek for new directions and methods to tackle these challenges.
We seek fresh thinking on analysis, prediction, and recommendation in the context of stochastic process mining, explicitly considering the likelihood of behavior in event logs, process models and languages.
The brainstorm seminar was organized as a satellite event of BPM’2023 in the center of Utrecht on September 9-10, 2023.