Advancements and Challenges in Object-Centric Process Mining: A Systematic Literature Review

TL;DR

This paper systematically reviews the development, current state, and challenges of object-centric process mining, highlighting its potential and the barriers to real-world adoption.

Contribution

It offers a comprehensive overview of object-centric process mining, analyzing its evolution, current challenges, and future research directions.

Findings

Object-centric process mining addresses limitations of traditional methods.

Limited adoption of object-centric techniques in real-world applications.

Identifies key challenges and research gaps in the field.

Abstract

Recent years have seen the emergence of object-centric process mining techniques. Born as a response to the limitations of traditional process mining in analyzing event data from prevalent information systems like CRM and ERP, these techniques aim to tackle the deficiency, convergence, and divergence issues seen in traditional event logs. Despite the promise, the adoption in real-world process mining analyses remains limited. This paper embarks on a comprehensive literature review of object-centric process mining, providing insights into the current status of the discipline and its historical trajectory.