Computer Science Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1593

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Subject: search.filters.subject.visualization design

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    A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation
    (Association for Computer Machinery (ACM), 2023-04-23) Zeng, Zhua; Battle, Leilani
    Selecting appropriate visual encodings is critical to designing effective visualization recommendation systems, yet few findings from graphical perception are typically applied within these systems. We observe two significant limitations in translating graphical perception knowledge into actionable visualization recommendation rules/constraints: inconsistent reporting of findings and a lack of shared data across studies. How can we translate the graphical perception literature into a knowledge base for visualization recommendation? We present a review of 59 papers that study user perception and performance across ten visual analysis tasks. Through this study, we contribute a JSON dataset that collates existing theoretical and experimental knowledge and summarizes key study outcomes in graphical perception. We illustrate how this dataset can inform automated encoding decisions with three representative visualization recommendation systems. Based on our findings, we highlight open challenges and opportunities for the community in collating graphical perception knowledge for a range of visualization recommendation scenarios.
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    User-Driven Support for Visualization Prototyping in D3
    (Association for Computer Machinery (ACM), 2023-03) Bako, Hannah K.; Varma, Alisha; Faboro, Anuoluwapo; Haider, Mahreen; Nerrise, Favour; Kenah, Bissaka; Dickerson, John P.; Battle, Leilani
    Templates have emerged as an effective approach to simplifying the visualization design and programming process. For example, they enable users to quickly generate multiple visualization designs even when using complex toolkits like D3. However, these templates are often treated as rigid artifacts that respond poorly to changes made outside of the template’s established parameters, limiting user creativity. Preserving the user’s creative flow requires a more dynamic approach to template-based visualization design, where tools can respond gracefully to users’ edits when they modify templates in unexpected ways. In this paper, we leverage the structural similarities revealed by templates to design resilient support features for prototyping D3 visualizations: recommendations to suggest complementary interactions for a users’ D3 program; and code augmentation to implement recommended interactions with a single click, even when users deviate from pre-defined templates. We demonstrate the utility of these features in Mirny, a designfocused prototyping environment for D3. In a user study with 20 D3 users, we find that these automated features enable participants to prototype their design ideas with significantly fewer programming iterations. We also characterize key modification strategies used by participants to customize D3 templates. Informed by our findings and participants’ feedback, we discuss the key implications of the use of templates for interleaving visualization programming and design.