Object-centric Processes with Structured Data and Exact Synchronization (Extended Version)

TL;DR

The paper addresses the limitation of existing object-centric process formalisms by introducing data-aware OPIDs (DOPIDs) that unify object identities, relationships, and rich data types with full synchronization capabilities. DOPIDs extend OPIDs to support structured data domains, object lists, and guards over arithmetic and uninterpreted functions, enabling complex synchronization patterns including exact synchronization. Conformance checking is operationalized via SMT-based encodings that handle data, object inscriptions, and synchronization, demonstrated through a proof-of-concept implementation integrated into a conformance tool. The work situates DOPIDs among related formalisms (e.g., DPNs, synchronous proclets, PNIDs) and outlines future directions for experimental evaluation and discovery techniques.

Abstract

Real-world processes often involve interdependent objects that also carry data values, such as integers, reals, or strings. However, existing process formalisms fall short to combine key modeling features, such as tracking object identities, supporting complex datatypes, handling dependencies among them, and object-aware synchronization. Object-centric Petri nets with identifiers (OPIDs) partially address these needs but treat objects as unstructured identifiers (e.g., order and item IDs), overlooking the rich semantics of complex data values (e.g., item prices or other attributes). To overcome these limitations, we introduce data-aware OPIDs (DOPIDs), a framework that strictly extends OPIDs by incorporating structured data manipulation capabilities, and full synchronization mechanisms. In spite of the expressiveness of the model, we show that it can be made operational: Specifically, we define a novel conformance checking approach leveraging satisfiability modulo theories (SMT) to compute data-aware object-centric alignments.