  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.
