A semantic approach for business process model abstraction

Abstract

Models of business processes can easily become large and difficult to understand. Abstraction has proven to be an effective means to present a readable, high-level view of a business process model, by showing aggregated activities and leaving out irrelevant details. Yet, it is an open question how to combine activities into high-level tasks in a way that corresponds to such actions by experienced modelers. In this paper, an approach is presented that exploits semantic information within a process model, beyond structural information, to decide on which activities belong to one another. In an experimental validation, we used an industrial process model repository to compare this approach with actual modeling decisions, showing a strong correlation between the two. As such, this paper contributes to the development of modeling support for the application of effective process model abstraction, easing the use of business process models in practice. © 2011 Springer-Verlag.