Modeling and Reasoning over Declarative Data-Aware Processes with Object-Centric Behavioral Constraints

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Abstract

Existing process modeling notations ranging from Petri nets to BPMN have difficulties capturing the data manipulated by processes. Process models often focus on the control flow, lacking an explicit, conceptually well-founded integration with real data models, such as ER diagrams or UML class diagrams. To overcome this limitation, Object-Centric Behavioral Constraints (OCBC) models were recently proposed as a new notation that combines full-fledged data models with control-flow constraints inspired by declarative process modeling notations such as DECLARE and DCR Graphs. We propose a formalization of the OCBC model using temporal description logics. The obtained formalization allows us to lift all reasoning services defined for constraint-based process modeling notations without data, to the much more sophisticated scenario of OCBC. Furthermore, we show how reasoning over OCBC models can be reformulated into decidable, standard reasoning tasks over the corresponding temporal description logic knowledge base.

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Artale, A., Kovtunova, A., Montali, M., & van der Aalst, W. M. P. (2019). Modeling and Reasoning over Declarative Data-Aware Processes with Object-Centric Behavioral Constraints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11675 LNCS, pp. 139–156). Springer Verlag. https://doi.org/10.1007/978-3-030-26619-6_11

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