A Survey of Approaches for Event Sequence Analysis and Visualization using the ESeVis Framework

TL;DR

This paper reviews various methods for analyzing and visualizing event sequence data, proposing the ESeVis framework to unify approaches from information visualization and process mining, highlighting opportunities for future integration.

Contribution

It introduces the ESeVis framework that integrates event sequence analysis techniques from information visualization and process mining into a unified perspective.

Findings

Mapped existing techniques to the ESeVis framework

Identified synergies between visualization and process mining

Provided a comprehensive overview of event sequence analysis methods

Abstract

Event sequence data is increasingly available. Many business operations are supported by information systems that record transactions, events, state changes, message exchanges, and so forth. This observation is equally valid for various industries, including production, logistics, healthcare, financial services, education, to name but a few. The variety of application areas explains that techniques for event sequence data analysis have been developed rather independently in different fields of computer science. Most prominent are contributions from information visualization and from process mining. So far, the contributions from these two fields have neither been compared nor have they been mapped to an integrated framework. In this paper, we develop the Event Sequence Visualization framework (ESeVis) that gives due credit to the traditions of both fields. Our mapping study provides an integrated perspective on both fields and identifies potential for synergies for future research.