Process Mining Reloaded: Event Structures as a Unified Representation of Process Models and Event Logs

Abstract

Process mining is a family of methods to analyze event logs produced during the execution of business processes in order to extract insights regarding their performance and conformance with respect to normative or expected behavior. The landscape of process mining methods and use cases has expanded considerably in the past decade. However, the field has evolved in a rather ad hoc manner without a unifying foundational theory that would allow algorithms and theoretical results developed for one process mining problem to be reused when addressing other related problems. In this paper we advocate a foundational approach to process mining based on a well-known model of concurrency, namely event structures. We outline how event structures can serve as a unified representation of behavior captured in process models and behavior captured in event logs. We then sketch how process mining operations, specifically automated process discovery, conformance checking and deviance mining, can be recast as operations on event structures.