Litcius/Paper detail

Accessibility for Color Vision Deficiencies: Challenges and Findings of a Large Scale Study on Paper Figures

Katrin Angerbauer, Nils Rodrigues, René Cutura, Seyda Öney, Nelusa Pathmanathan, Cristina Morariu, Daniel Weiskopf, Michael Sedlmair

2022CHI Conference on Human Factors in Computing Systems32 citationsDOI

Abstract

We present an exploratory study on the accessibility of images in publications when viewed with color vision deficiencies (CVDs). The study is based on 1,710 images sampled from a visualization dataset (VIS30K) over five years. We simulated four CVDs on each image. First, four researchers (one with a CVD) identified existing issues and helpful aspects in a subset of the images. Based on the resulting labels, 200 crowdworkers provided 30,000 ratings on present CVD issues in the simulated images. We analyzed this data for correlations, clusters, trends, and free text comments to gain a first overview of paper figure accessibility. Overall, about 60 % of the images were rated accessible. Furthermore, our study indicates that accessibility issues are subjective and hard to detect. On a meta-level, we reflect on our study experience to point out challenges and opportunities of large-scale accessibility studies for future research directions.

Topics & Concepts

Computer scienceScale (ratio)VisualizationPoint (geometry)Exploratory researchArtificial intelligenceData scienceImage (mathematics)Computer visionCartographyGeographyMathematicsGeometrySociologyAnthropologyTactile and Sensory InteractionsData Visualization and AnalyticsMobile Crowdsensing and Crowdsourcing