Time and Relations into Focus: Ontological Foundations of Object-Centric Event Data

2025-12-16

AI Summary

Existing case-centric event data models inadequately represent multi-object interactions and dynamic temporal relationships, while mainstream Object-Centered Event Data (OCED) models suffer from semantic ambiguity, weak temporal modeling, and insufficient expression of evolving object relationships. Method: This paper proposes gOCED—an ontology-driven meta-model for OCED—that introduces the lightweight foundational ontology gUFO to OCED modeling for the first time. It systematically integrates four semantic dimensions: objects, events, time, and dynamic relationships, via ontological analysis, extension of the OCED Core Model, formal semantic specification, and empirical validation through use cases. Contribution/Results: gOCED delivers an unambiguous, extensible, and unified representation framework that comprehensively subsumes and surpasses existing OCED approaches. It enables precise modeling of complex object interdependencies, explicit temporal constraints, and evolution-aware relational dynamics, thereby advancing the theoretical foundations and practical expressiveness of OCED.

Technology Category

• Knowledge Representation and Reasoning: Ontologies
• Reasoning under Uncertainty: Relational Probabilistic Models
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data

Application Category

• Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semantics
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Web Mining and Content Analysis: Models for Web evolution

Abstract

Object-centric process mining is a new branch of process mining where events are associated with multiple objects, and where object-to-object interactions are essential to understand the process dynamics. Traditional event data models, also called case-centric, are unable to cope with the complexity introduced by these more refined relationships. Several models have been made to move from case-centric to Object-Centric Event Data (OCED), trying to retain simplicity as much as possible. Still, these suffer from inherent ambiguities, and lack a comprehensive support of essential dimensions related to time and (dynamic) relations. In this work, we propose to fill this gap by leveraging a well-founded ontology of events and bringing ontological foundations to OCED, with a three-step approach. First, we start from key open issues reported in the literature regarding current OCED metamodels, and witness their ambiguity and expressiveness limitations on illustrative and representative examples proposed therein. Second, we consider the OCED Core Model, currently proposed as the basis for defining a new standard for object-centric event data, and we enhance it by grounding it on a lightweight version of UFO-B called gUFO, a well-known foundational ontology tailored to the representation of objects, events, time, and their (dynamic) relations. This results in a new metamodel, which we call gOCED. The third contribution then shows how gOCED at once covers the features of existing metamodels preserving their simplicity, and extends them with the essential features needed to overcome the ambiguity and expressiveness issues reported in the literature.

Problem

• Addresses ambiguity in object-centric event data models
• Enhances support for time and dynamic relations in process mining
• Overcomes expressiveness limitations of existing event data metamodels

Innovation

• Leverages UFO-B foundational ontology for OCED
• Introduces gOCED metamodel to overcome ambiguity
• Extends OCED Core Model with time and relations