Understanding how Designers Find and Use Data Visualization Examples

Hannah K. Bako, Xinyi Liu, Leilani Battle, Zhicheng Liu

View presentation:2022-10-20T20:00:00ZGMT-0600Change your timezone on the schedule page
2022-10-20T20:00:00Z
Exemplar figure, described by caption below
A graphic showing key themes for a paper titled "Understanding how designers find and use data visualization examples". At the top right is a graphic of a young man and lady depicting the two key groups of visualization designers in this study. Below is a collage of images with a magnifying glass depicting the search for examples with the caption "exploratory vs targeted search". In the middle is a graphic of a puzzled person trying to evaluate the criteria for selecting examples with the caption "effectiveness vs aesthetics". On the far right is a graphic depicting ideas being transferred between examples and visualization designs captioned " strategies for using examples, Select & Merge, Replicate & Modify, Trial & Error".

Prerecorded Talk

The live footage of the talk, including the Q&A, can be viewed on the session page, Reflecting on Academia and our Field.

Fast forward
Abstract

Examples are useful for inspiring ideas and facilitating implementation in visualization design. However, there is little understanding of how visualization designers use examples, and how computational tools may support such activities. In this paper, we contribute an exploratory study of current practices in incorporating visualization examples. We conducted semi-structured interviews with 15 university students and 15 professional designers. Our analysis focus on two core design activities: searching for examples and utilizing examples. We characterize observed strategies and tools for performing these activities, as well as major challenges that hinder designers’ current workflows. In addition, we identify themes that cut across these two activities: criteria for determining example usefulness, curation practices, and design fixation. Given our findings, we discuss the implications for visualization design and authoring tools and highlight critical areas for future research.