Review of Visual Encodings in Common Process Mining Tools

dc.contributor.authorKnoblich, Stevenen_US
dc.contributor.authorMendling, Janen_US
dc.contributor.authorJambor, Helenaen_US
dc.contributor.editorArleo, Alessioen_US
dc.contributor.editorvan den Elzen, Stefen_US
dc.contributor.editorvon Landesberger, Tatianaen_US
dc.contributor.editorRehse, Jana-Rebeccaen_US
dc.contributor.editorPufahl, Luiseen_US
dc.contributor.editorZerbato, Francescaen_US
dc.description.abstractProcess mining tools empower process analysts to scrutinize business processes by leveraging algorithmic techniques and event log datasets. To support the analysis of inefficiencies of business processes, different types of visualization techniques have been introduced for process mining. These techniques enhance process models by incorporating performance data, for instance to highlight activity duration by using gradational color palettes, and by mapping statistical parameters as text notes directly into the model. So far, tool vendors have designed a diverse spectrum of visual features for enhancing models, but research has not systematically provided insights into their mutual effectiveness. In this paper, we review the visualizations of six common business process mining tools. To account for the variability in the visual display, we expanded existing taxonomies for evaluating event sequences with marks and channels as well as accessibility dimensions, each important for end-user comprehension. Then, we performed an expert survey to assess the legibility of the visualizations to test the validity of our expanded taxonomy. In this way, we demonstrate the potential for improving process mining visualizations to expand its value in today's process mining tools.en_US
dc.description.seriesinformationVIPRA 2024 - Visual Process Analytics Workshop
dc.identifier.pages6 pages
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.subjectCCS Concepts: Human-centered computing → Visual analytics; Visual analytics
dc.subjectHuman centered computing → Visual analytics
dc.subjectVisual analytics
dc.titleReview of Visual Encodings in Common Process Mining Toolsen_US
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