2025/10/07 by Abdur Rehman Anwar Qureshi, Adrian Rebmann, Qureshi, Abdur Rehman Anwar +7
Business, Management and Accounting · Computer Science · #Business Process Modeling and Analysis #Databases (cs.DB) #FOS: Computer and information sciences #Semantic Web and Ontologies #Service-Oriented Architecture and Web Services #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2510.06414
openalex publication_date 2025/10/07 · openalex created_date 2025/10/18 · openalex updated_date 2026/07/28
Business process management is increasingly practiced using data-driven approaches. Still, classical imperative process models, which are typically formalized using Petri nets, are not straightforwardly applicable to the relational databases that contain much of the available structured process execution data. This creates a gap between the traditional world of process modeling and recent developments around data-driven process analysis, ultimately leading to the under-utilization of often readily available process models. In this paper, we close this gap by providing an approach for translating imperative models into relaxed process data queries, specifically SQL queries executable on relational databases, for conformance checking. Our results show the continued relevance of imperative process models to data-driven process management, as well as the importance of behavioral footprints and other declarative approaches for integrating model-based and data-driven process management.