Object-Centric Behavioral Constraints
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Abstract (arXiv)
Today's process modeling languages often force the analyst or modeler to straightjacket real-life processes into simplistic or incomplete models that fail to capture the essential features of the domain under study. Conventional business process models only describe the lifecycles of individual instances (cases) in isolation. Although process models may include data elements (cf. BPMN), explicit connections to real data models (e.g., an entity relationship model or a UML class model) are rarely made. Therefore, we propose a novel approach that extends data models with a behavioral perspective. Data models can easily deal with many-to-many and one-to-many relationships. This is exploited to create process models that can also model complex interactions between different types of instances. Classical multiple-instance problems are circumvented by using the data model for event correlation. The declarative nature of the proposed language makes it possible to model behavioral constraints over activities like cardinality constraints in data models. The resulting object-centric behavioral constraint (OCBC) model is able to describe processes involving interacting instances and complex data dependencies. In this paper, we introduce the OCBC model and notation, providing a number of examples that give a flavour of the approach. We then define a set-theoretic semantics exploiting cardinality constraints within and across time points. We finally formalize conformance checking in our setting, arguing that evaluating conformance against OCBC models requires diagnostics that go beyond what is provided by contemporary conformance checking approaches.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Mar 2017.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1.
4 papers.
- 2021Precision and Fitness in Object-Centric Process Miningcited by 9
- 2022OPerA: Object-Centric Performance Analysiscited by 4
- 2023Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Versioncited by 1
- 2024Extracting Process-Aware Decision Models from Object-Centric Process Datacited by 1
- 2024Extracting Process-Aware Decision Models from Object-Centric Process Data26 Jan 2024
- 2023Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Version29 Mar 2023
- 2022OPerA: Object-Centric Performance Analysis22 Apr 2022
- 2021Precision and Fitness in Object-Centric Process Mining6 Oct 2021