Object-Centric Conformance Alignments with Synchronization (Extended Version)

TL;DR

This work tackles conformance checking for object-centric processes where object identity and inter-object synchronization matter. It introduces Object-Centric Petri Nets with Identifiers (OPIDs), combining object-centric nets and PNIDs to support multi-object relations and subset synchronization, while enabling alignment-based conformance. The authors formalize the conformance task, provide an SMT encoding for optimal alignments, implement a tool (oCoCoMoT), and validate practicality on literature data, demonstrating feasibility despite higher overhead. By enabling precise tracking of object correspondences in logs, the approach improves detection of deviations in complex inter-object processes and supports more accurate process mining for real-world data.

Abstract

Real-world processes operate on objects that are inter-dependent. To accurately reflect the nature of such processes, object-centric process mining techniques are needed, notably conformance checking. However, while the object-centric perspective has recently gained traction, few concrete process mining techniques have been presented so far. Moreover, existing approaches are severely limited in their abilities to keep track of object identity and object dependencies. Consequently, serious problems in logs remain undetected. In this paper, we present a new formalism that combines the key modelling features of two existing approaches, in particular the ability of object-centric Petri nets to capture one-to-many relations and the one of Petri nets with identifiers to compare and synchronize objects based on their identity. We call the resulting formalism 'object-centric Petri nets with identifiers', and define alignments and the conformance checking task for this setting. We propose a conformance checking approach for such nets based on an encoding in satisfiability modulo theories (SMT), and illustrate how it can be effectively used to overcome shortcomings of earlier work. To assess its practicality, we perform an evaluation on data from the literature.