Object-Centric Analysis of XES Event Logs: Integrating OCED Modeling with SPARQL Queries

2025-11-01

AI Summary

The eXtensible Event Stream (XES) standard lacks explicit support for multi-object interactions and semantic dependencies, limiting the depth of process mining. To address this, we propose an object-oriented event data modeling approach: we reconstruct event logs based on the Object-Centric Event Data Ontology (OCEDO), explicitly representing implicit object relationships as formal ontology structures, and integrate SPARQL-based semantic querying to enable fine-grained behavioral dependency analysis and cross-object relational inference. Experiments on the BPIC 2013 dataset demonstrate that our method significantly improves event log completeness and interpretability. It supports object-level interaction modeling and deep process insights—capabilities unattainable with conventional sequential models. By bridging ontological semantics with process mining, the approach establishes a scalable, semantically enriched infrastructure for object-centric process mining.

Technology Category

• Data Mining & Knowledge Management: Intelligent Query Processing
• Knowledge Representation and Reasoning: Description Logics
• Machine Learning: Time-Series/Data Streams

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
• Web Mining and Content Analysis: Bridging structured and unstructured data
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

Object Centric Event Data (OCED) has gained attention in recent years within the field of process mining. However, there are still many challenges, such as connecting the XES format to object-centric approaches to enable more insightful analysis. It is important for a process miner to understand the insights and dependencies of events in the event log to see what is going on in our processes. In previous standards, the dependencies of event logs are only used to show events, but not their dependencies among each other and actions in detail as described in OCEDO. There is more information in the event log when it is revealed using the OCEDO model. It becomes more understandable and easier to grasp the concepts and deal with the processes. This paper proposes the use of Object-Centric Event Data Ontology (OCEDO) to overcome the limitations of the XES standard in event logs for process mining. We demonstrate how the OCEDO approach, integrated with SPARQL queries, can be applied to the BPIC 2013 dataset to make the relationships between events and objects more explicit. It describes dealing with the meta descriptions of the OCEDO model on a business process challenge as an event log. It improves the completeness and readability of process data, suggesting that object-centric modeling allows for richer analyses than traditional approaches.

Problem

• Overcoming XES standard limitations for object-centric process mining analysis
• Making relationships between events and objects more explicit in logs
• Improving completeness and readability of process data through OCEDO modeling

Innovation

• OCEDO ontology overcomes XES standard limitations
• Integrates OCED modeling with SPARQL queries
• Reveals explicit event-object relationships in processes