An official website of the United States government
Scatterplots commonly use multiple visual channels to encode multivariate datasets. Such visualizations often use size, shape, and color as these dimensions are considered separable--dimensions represented by one channel do not significantly interfere with viewers' abilities to perceive data in another. However, recent work shows the size of marks significantly impacts color difference perceptions, leading to broader questions about the separability of these channels. In this paper, we present a series of crowdsourced experiments measuring how mark shape, size, and color influence data interpretation in multiclass scatterplots. Our results indicate that mark shape significantly influences color and size perception, and that separability among these channels functions asymmetrically: shape more strongly influences size and color perceptions in scatterplots than size and color influence shape. Models constructed from the resulting data can help designers anticipate viewer perceptions to build more effective visualizations.
more »
« less
Revisiting Categorical Color Perception in Scatterplots: Sequential, Diverging, and Categorical Palettes
Existing guidelines for categorical color selection are heuristic, often grounded in intuition rather than empirical studies of readers' abilities. While design conventions recommend palettes maximize hue differences, more recent exploratory findings indicate other factors, such as lightness, may play a role in effective categorical palette design. We conducted a crowdsourced experiment on mean value judgments in multi-class scatterplots using five color palette families-single-hue sequential, multihue sequential, perceptually-uniform multi-hue sequential, diverging, and multi-hue categorical-that differ in how they manipulate hue and lightness. Participants estimated relative mean positions in scatterplots containing 2 to 10 categories using 20 colormaps. Our results confirm heuristic guidance that hue-based categorical palettes are most effective. However, they also provide additional evidence that scalable categorical encoding relies on more than hue variance.
more »
« less
- Award ID(s):
- 2320920
- PAR ID:
- 10533072
- Publisher / Repository:
- The Eurographics Association
- Date Published:
- ISSN:
- 1727-5296
- Subject(s) / Keyword(s):
- CCS Concepts: Human-centered computing → Information visualization Empirical studies in visualization Human centered computing → Information visualization Empirical studies in visualization
- Format(s):
- Medium: X Size: 5 pages
- Size(s):
- 5 pages
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
It is well established that skin lightness-darkness is associated with social outcomes, but little is known regarding the social salience of skin undertones (redness and yellowness). Our study addresses two related research questions on this topic: first, we ask whether red and yellow undertones are consistently perceived by observers; second, we ask whether red and yellow undertones are associated with expectations of discrimination across a range of social settings. We address these questions using novel survey data in which skin lightness-darkness and undertones are captured using CIELAB measurements and a two-dimensional categorical skin color scale. Although we find skin lightness-darkness to be the strongest and most consistent predictor of discrimination expectations, respondents also perceived skin undertones consistently, and skin yellowness was associated with a higher predicted likelihood of discrimination net of lightness-darkness in certain social settings. Our findings suggest that colorism can extend beyond a light-dark binary and emphasize the value of capturing undertones, particularly yellowness, in social surveys assessing skin color.more » « less
-
Geographical maps encoded with rainbow color scales are widely used for spatial data analysis in climate science, despite evidence from the visualization literature that they are not perceptually optimal. We present a controlled user study that compares the effect of color scales on performance accuracy for climate-modeling tasks using pairs of continuous geographical maps generated using climatological metrics. For each pair of maps, 39 scientist-observers judged: i) the magnitude of their difference, ii) their degree of spatial similarity, and iii) the region of greatest dissimilarity between them. Besides the rainbow color scale, two other continuous color scales were chosen such that all three of them covaried two dimensions (luminance monotonicity and hue banding), hypothesized to have an impact on visual performance. We also analyzed subjective performance measures, such as user confidence, perceived accuracy, preference, and familiarity in using the different color scales. We found that monotonic luminance scales produced significantly more accurate judgments of magnitude difference but were not superior in spatial comparison tasks, and that hue banding had differential effects based on the task and conditions. Scientists expressed the highest preference and perceived confidence and accuracy with the rainbow, despite its poor performance on the magnitude comparison tasks.more » « less
-
Zhou, Xuming (Ed.)Abstract Comparative genomics approaches seek to associate molecular evolution with the evolution of phenotypes across a phylogeny. Many of these methods lack the ability to analyze non-ordinal categorical traits with more than two categories. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogeny-aware permutations, “permulations”, on categorical traits. We demonstrate our new method on a three-category diet phenotype, and we compare its performance to binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We present an analysis of how the categorical permulations scale with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotypes and that the categorical ancestral state reconstruction drives an improvement in our ability to capture diet-related enriched pathways compared to binary RERconverge when implemented without user input on phenotype evolution. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution than have previously been analyzed.more » « less
-
null (Ed.)Abstract Categorical induction abilities are robust in typically developing (TD) preschoolers, while children with Autism Spectrum Disorders (ASD) frequently perform inconsistently on tasks asking for the transference of traits from a known category member to a new example based on shared category membership. Here, TD five-year-olds and six-year-olds with ASD participated in a categorical induction task; the TD children performed significantly better and more consistently than the children with ASD. Concurrent verbal and nonverbal tests were not significant correlates; however, the TD children's shape bias performance at two years of age was significantly positively predictive of categorical induction performance at age five. The shape bias, the tendency to extend a novel label to other objects of the same shape during word learning, appears linked with categorical induction ability in TD children, suggesting a common underlying skill and consistent developmental trajectory. Word learning and categorical induction appear uncoupled in children with ASD.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.2312/evs.20241073
