An XES Extension for Uncertain Event Data

TL;DR

This paper introduces an extension to the XES event data standard that allows for representing, processing, and analyzing uncertain event data, addressing noise, errors, and missing information in process mining logs.

Contribution

It presents a novel extension to the XES standard enabling the handling of uncertain event data for process mining tasks.

Findings

Supports input, output, and manipulation of uncertain data

Enables analysis through process discovery and conformance checking

Facilitates better handling of noisy and incomplete logs

Abstract

Event data, often stored in the form of event logs, serve as the starting point for process mining and other evidence-based process improvements. However, event data in logs are often tainted by noise, errors, and missing data. Recently, a novel body of research has emerged, with the aim to address and analyze a class of anomalies known as uncertainty-imprecisions quantified with meta-information in the event log. This paper illustrates an extension of the XES data standard capable of representing uncertain event data. Such an extension enables input, output, and manipulation of uncertain data, as well as analysis through the process discovery and conformance checking approaches available in literature.