An XES Extension for Uncertain Event Data

arXiv (Cornell University), pp. 116–120

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.

Authors 3

1. Marco Pegoraro Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen

2. Merih Seran Uysal Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen

3. Wil M. P. van der Aalst Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen