Year: 2025
Type: article
Abstract: Data visualization plays a crucial role in enhancing the communication capabilities of information systems through high-quality visual diagrams. Traditional techniques for depicting set intersections, i.e., Euler and Venn diagrams, offer limited information density and scalability. This paper examines an alternative approach, UpSet, which provides richer informational output and has gained acceptance across various disciplines. Despite its wide adoption, the Information Systems (IS) community has not yet fully recognized UpSet's potential. We introduce UpSet to the IS audience, demonstrating its utility through academic and business examples relevant to IS. Additionally, we discuss its general applicability in research, highlighting how UpSet can significantly improve set-intersecting visualization.
Authors: Song, Yuanyuan, Tuczek, Matthias, Watson, Richard T.
Institutions: Marquette University, Leibniz University Hannover
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7006634859
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