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• W2796347334 abstract "An essential goal of quantitative color encoding is the accurate mapping of perceptual dimensions of color to the logical structure of data. Prior research identifies weaknesses of 'rainbow' colormaps and advocates for ramping in luminance, while recent work contributes multi-hue colormaps generated using perceptually-uniform color models. We contribute a comparative analysis of different colormap types, with a focus on comparing single- and multi-hue schemes. We present a suite of experiments in which subjects perform relative distance judgments among color triplets drawn systematically from each of four single-hue and five multi-hue colormaps. We characterize speed and accuracy across each colormap, and identify conditions that degrade performance. We also find that a combination of perceptual color space and color naming measures more accurately predict user performance than either alone, though the overall accuracy is poor. Based on these results, we distill recommendations on how to design more effective color encodings for scalar data." @default.
• W2796347334 created "2018-04-13" @default.
• W2796347334 creator A5023363049 @default.
• W2796347334 creator A5090570042 @default.
• W2796347334 date "2018-04-21" @default.
• W2796347334 modified "2023-10-01" @default.
• W2796347334 title "Somewhere Over the Rainbow" @default.
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• W2796347334 doi "https://doi.org/10.1145/3173574.3174172" @default.
• W2796347334 hasPublicationYear "2018" @default.
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