Transforming Object-Centric Event Logs to Temporal Event Knowledge Graphs (Extended Version)

TL;DR

This paper introduces Temporal Event Knowledge Graphs (tEKG) to incorporate attribute changes over time in object-centric event logs, and presents an algorithm to transform OCEL 2.0 logs into tEKG for enhanced process analysis.

Contribution

It proposes a novel framework and algorithm for converting OCEL 2.0 logs into temporal knowledge graphs that account for dynamic attribute changes.

Findings

tEKG effectively models attribute changes over time.

The transformation algorithm enables richer process analysis.

Enhanced understanding of object interactions over time.

Abstract

Event logs play a fundamental role in enabling data-driven business process analysis. Traditionally, these logs track events related to a single object, known as the case, limiting the scope of analysis. Recent advancements, such as Object-Centric Event Logs (OCEL) and Event Knowledge Graphs (EKG), capture better how events relate to multiple objects. However, attributes of objects can change over time, which was not initially considered in OCEL or EKG. While OCEL 2.0 has addressed some of these limitations, there remains a research gap concerning how attribute changes should be accommodated in EKG and how OCEL 2.0 logs can be transformed into EKG. This paper fills this gap by introducing Temporal Event Knowledge Graphs (tEKG) and defining an algorithm to convert an OCEL 2.0 log to a tEKG.