Color encoding is foundational to visualizing quantitative data. Guidelines for colormap design have traditionally emphasized perceptual principles, such as order and uniformity. However, colors also evoke cognitive and linguistic associations whose role in data interpretation remains underexplored. We study how two linguistic factors, name salience and name variation, affect people's ability to draw inferences from spatial visualizations. In two experiments, we found that participants are better at interpreting visualizations when viewing colors with more salient names (e.g., prototypical ‘blue’, ‘yellow’, and ‘red’ over ‘teal’, ‘beige’, and ‘maroon’). The effect was robust across four visualization types, but was more pronounced in continuous (e.g., smooth geographical maps) than in similar discrete representations (e.g., choropleths). Participants' accuracy also improved as the number of nameable colors increased, although the latter had a less robust effect. Our findings suggest that color nameability is an important design consideration for quantitative colormaps, and may even outweigh traditional perceptual metrics. In particular, we found that the linguistic associations of color are a better predictor of performance than the perceptual properties of those colors. We discuss the implications and outline research opportunities. The data and materials for this study are available at https://osf.io/asb7n

中文翻译：

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颜色可命名性预测空间可视化中的推理准确度

颜色编码是可视化定量数据的基础。颜色图设计指南传统上强调感知原则，例如顺序和均匀性。然而，颜色也会唤起认知和语言关联，其在数据解释中的作用仍未得到充分探索。我们研究了名称显着性和名称变异这两个语言因素如何影响人们从空间可视化中得出推论的能力。在两个实验中，我们发现参与者在查看具有更显着名称的颜色（例如，原型“蓝色”、“黄色”和“红色”而不是“蓝绿色”、“米色”和“栗色”）时更能解释可视化效果. 这种效果在四种可视化类型中都很稳健，但在连续（例如，平滑的地理地图）中比在类似的离散表示（例如，等值线图）中更为明显。随着可命名颜色数量的增加，参与者的准确性也有所提高，尽管后者的效果不太明显。我们的研究结果表明，颜色可命名性是定量颜色图的重要设计考虑因素，甚至可能超过传统的感知指标。特别是，我们发现颜色的语言关联比这些颜色的感知属性更能预测性能。我们讨论了影响并概述了研究机会。本研究的数据和材料可在 https://osf.io/asb7n 获得 甚至可能超过传统的感知指标。特别是，我们发现颜色的语言关联比这些颜色的感知属性更能预测性能。我们讨论了影响并概述了研究机会。本研究的数据和材料可在 https://osf.io/asb7n 获得 甚至可能超过传统的感知指标。特别是，我们发现颜色的语言关联比这些颜色的感知属性更能预测性能。我们讨论了影响并概述了研究机会。本研究的数据和材料可在 https://osf.io/asb7n 获得