Accessible Text Descriptions for UpSet Plots
Ishrat Jahan Eliza - University of Utah, Salt Lake City, United States
Jake Wagoner - University of Utah, Salt Lake City, United States
Jack Wilburn - University of Utah, Salt Lake City, United States
Nate Lanza - Scientific Computing and Imaging Institute, Salt Lake City, United States
Daniel Hajas - University College London, London, United Kingdom
Alexander Lex - University of Utah, Salt Lake City, United States
Room: Bayshore V
2024-10-13T12:30:00ZGMT-0600Change your timezone on the schedule page
2024-10-13T12:30:00Z
Abstract
Data visualizations are typically not accessible to blind and low-vision users. The most widely used remedy for making data visualizations accessible is text descriptions. Yet, manually creating useful text descriptions is often omitted by visualization authors, either because of a lack of awareness or a perceived burden. Automatically generated text descriptions are a potential partial remedy. However, with current methods it is unfeasible to create text descriptions for complex scientific charts. In this paper, we describe our methods for generating text descriptions for one complex scientific visualization: the UpSet plot. UpSet is a widely used technique for the visualization and analysis of sets and their intersections. At the same time, UpSet is arguably unfamiliar to novices and used mostly in scientific contexts. Generating text descriptions for UpSet plots is challenging because the patterns observed in UpSet plots have not been studied. We first analyze patterns present in dozens of published UpSet plots. We then introduce software that generates text descriptions for UpSet plots based on the patterns present in the chart. Finally, we introduce a web service that generates text descriptions based on a specification of an UpSet plot, and demonstrate its use in both an interactive web-based implementation and a static Python implementation of UpSet.