Opacity differences in layered visuals affect user accuracy variably
Evaluating Just Noticeable Differences in Layered Opacity Visualizations
Human-Computer Interaction
Summary
Opacity is used to show data in visuals, but it's less understood than color or size. Meng and colleagues found some color schemes work better with opacity. The authors tested how well people notice opacity changes across different ranges and colors. They saw most errors happen with very light or very dark opacities, and people performed similarly with different color schemes. Individuals varied a lot in how accurately they spotted these differences.
What this means in practice
- •For data visualization designers: Design better layered visuals by accounting for more errors in extreme opacity comparisons and individual user differences.
- •For user interface developers: Improve visual clarity by selecting opacity ranges where users perform more reliably, rather than using extremes.
Authors
Caterina Ponti, Shano Liang, Lane Harrison, Alark Joshi
Abstract
Opacity is a widely used channel in data visualization, but it remains less well understood compared to channels such as color, length, size, etc. Recent work from Meng et al. investigated the impact of opacity across competing color schemes, finding that certain color schemes were associated with better participant accuracy. We examine these effects further in a controlled two-alternative forced-choice setup to determine whether opacity differences are truly equal across possible opacity comparison ranges. In a within-subjects study with 96 trials, including two competing color schemes (best and worst from Meng et al.) and 48 opacity pairs, we find little differences between color schemes but larger individual differences in accuracy. Further, results show stable performance in middle opacity ranges, with more errors occurring when comparing extreme values. We discuss potential implications for design guidelines and further study and make our study materials, analysis scripts, and data available at https://osf.io/zv9dx/overview?view_only=38d03cea1b3d42788593e3e6b1016cfd.