POWL: Partially Ordered Workflow Language

Process models are used to represent processes in order to support communication and allow for the simulation and analysis of the processes. Many real-life processes naturally define partial orders over the activities they are composed of. Partial orders can be used as a graph-like representation of process behavior. On the one hand, partially ordered graph representations allow us to easily model concurrent and sequential behavior between activities while ensuring simplicity and scalability. On the other hand, partial orders lack the support for typical process constructs such as choice and loop structures. Therefore, in this paper, we present a novel process modeling notation, i.e., the Partially Ordered Workflow Language (POWL). A POWL model is a partially ordered graph extended with control-flow operators for modeling choice and loop structures. A POWL model has a hierarchical structure; i.e., POWL models can be combined into a new model either using a control-flow operator or as a partial order. We propose an initial approach to demonstrate the feasibility of using POWL models for process discovery, and we evaluate our approach based on real-life data.