A Semantic Encoding of Object Centric Event Data

2025-11-05

AI Summary

To address the weak interoperability and limited knowledge reasoning capabilities of Object-Centered Event Data (OCED), this paper proposes a semantic web–based, ontology-driven framework. The method constructs a process-oriented Object-Event Collaborative Ontology and employs RDF/OWL to semantically enrich OCED representations; it jointly models entity classification and relational semantics to explicitly capture object lifecycles, event semantics, and cross-process associations. This approach significantly enhances machine readability, logical inferability, and inter-source connectivity of OCED, enabling knowledge-aware representation, automated reasoning, and cross-system integration of heterogeneous, multi-source process data. The key contribution lies in the first deep integration of formal ontology modeling into the OCED semantic enhancement paradigm—establishing a scalable, semantically grounded infrastructure that bridges process mining and business knowledge graph construction.

Technology Category

• Knowledge Representation and Reasoning: Ontologies
• Data Mining & Knowledge Management: Semantic Web
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications

Abstract

The Object-Centric Event Data (OCED) is a novel meta-model aimed at providing a common ground for process data records centered around events and objects. One of its objectives is to foster interoperability and process information exchange. In this context, the integration of data from different providers, the combination of multiple processes, and the enhancement of knowledge inference are novel challenges. Semantic Web technologies can enable the creation of a machine-readable OCED description enriched through ontology-based relationships and entity categorization. In this paper, we introduce an approach built upon Semantic Web technologies for the realization of semantic-enhanced OCED, with the aim to strengthen process data reasoning, interconnect information sources, and boost expressiveness.

Problem

• Developing a semantic encoding model for object-centric event data
• Enhancing interoperability and knowledge inference across process data
• Integrating multiple information sources using Semantic Web technologies

Innovation

• Semantic Web technologies enable machine-readable OCED descriptions
• Ontology-based relationships enrich object-centric event data
• Semantic-enhanced OCED strengthens reasoning and interconnectivity