Object-Centric Event Logs: Specifications, Comparative Analysis and Refinement

TL;DR

This paper analyzes various object-centric event log formats in process mining, proposing a specifications framework to improve interoperability, consistency, and understanding of log formats for enhanced research and practical applications.

Contribution

It introduces a comprehensive specifications framework for object-centric event logs, enabling comparison, evaluation, and refinement of existing formats to address interoperability challenges.

Findings

Identifies commonalities and discrepancies among object-centric log formats.

Highlights unresolved issues in log format standardization.

Proposes potential solutions for improving log format compatibility.

Abstract

Process mining aims to comprehend and enhance business processes by analyzing event logs. Recently, object-centric process mining has gained traction by considering multiple objects interacting with each other in a process. This object-centric approach offers advantages over traditional methods by avoiding dimension reduction issues. However, in contrast to traditional process mining where a standard event log format was quickly agreed upon with XES providing a common platform for further research and industry, various object-centric logging formats have been proposed, each addressing specific challenges such as object relations or dynamic attribute changes. This makes that interoperability of object-centric algorithms remains a challenge, hindering reproducibility and generalizability in research. Additionally, the object-centric process storage paradigm aligns well with a wide range of object-oriented databases storing process data. This paper introduces a specifications framework from three perspectives originating from process mining (what should be analyzed), object-centric process modeling (how it should be modeled), and database storage (how it should be stored) perspectives in order to compare and evaluate object-centric log formats. By identifying commonalities and discrepancies among these formats, the study delves into unresolved issues and proposes potential solutions. Ultimately, this research contributes to advancing object-centric process mining by facilitating a deeper understanding of event log formats and promoting consistency and compatibility across methodologies.