IEEE VIS 2024 Content: Unveiling How Examples Shape Data Visualization Design Outcomes

Unveiling How Examples Shape Data Visualization Design Outcomes

Hannah K. Bako - University of Maryland, College Park, United States

Xinyi Liu - The University of Texas at Austin, Austin, United States

Grace Ko - University of Maryland, College Park, United States

Hyemi Song - Human Data Interaction Lab, College Park, United States

Leilani Battle - University of Washington, Seattle, United States

Zhicheng Liu - University of Maryland, College Park, United States

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Room: Bayshore II

2024-10-17T16:12:00Z GMT-0600 Change your timezone on the schedule page
2024-10-17T16:12:00Z
Exemplar figure, described by caption below
The image outlines an exploratory study investigating how the timing and properties of examples influence visualization design outcomes, highlighting key stages from task introduction to final design selection.
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Keywords

data visualization, design, examples

Abstract

Visualization designers (e.g., journalists or data analysts) often rely on examples to explore the space of possible designs, yet we have little insight into how examples shape data visualization design outcomes. While the effects of examples have been studied in other disciplines, such as web design or engineering, the results are not readily applicable to visualization due to inconsistencies in findings and challenges unique to visualization design. Towards bridging this gap, we conduct an exploratory experiment involving 32 data visualization designers focusing on the influence of five factors (timing, quantity, diversity, data topic similarity, and data schema similarity) on objectively measurable design outcomes (e.g., numbers of designs and idea transfers). Our quantitative analysis shows that when examples are introduced after initial brainstorming, designers curate examples with topics less similar to the dataset they are working on and produce more designs with a high variation in visualization components. Also, designers copy more ideas from examples with higher data schema similarities. Our qualitative analysis of participants’ thought processes provides insights into why designers incorporate examples into their designs, revealing potential factors that have not been previously investigated. Finally, we discuss how our results inform how designers may use examples during design ideation as well as future research on quantifying designs and supporting example-based visualization design. All supplemental materials are available in our OSF repo.