Vipra2024

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/3607006

Browse

Browsing Vipra2024 by Subject "Visual analytics"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Review of Visual Encodings in Common Process Mining Tools
    (The Eurographics Association, 2024) Knoblich, Steven; Mendling, Jan; Jambor, Helena; Arleo, Alessio; van den Elzen, Stef; von Landesberger, Tatiana; Rehse, Jana-Rebecca; Pufahl, Luise; Zerbato, Francesca
    Process 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.
  • Thumbnail Image
    Item
    Visual Journey Analytics: Lessons Learned from Real-world Implementations
    (The Eurographics Association, 2024) Brath, Richard; Andersen, Paul; Matusiak, Martin; Gerber, Raymond; Arleo, Alessio; van den Elzen, Stef; von Landesberger, Tatiana; Rehse, Jana-Rebecca; Pufahl, Luise; Zerbato, Francesca
    Process mining and more broadly journey analytics create sequences that can be understood with graph-oriented visual analytics. We have designed and implemented more than a dozen visual analytics on sequence data in production software over the last 20 years. We outline a variety of data challenges, user tasks, visualization layouts, node and edge representations, and interactions, including strengths and weaknesses and potential future research.