To create effective data visualizations, it helps to represent data using visual features in intuitive ways. When visualization designs match observer expectations, visualizations are easier to interpret. Prior work suggests that several factors influence such expectations. For example, the dark-is-more bias leads observers to infer that darker colors map to larger quantities, and the opaque-is-more bias leads them to infer that regions appearing more opaque (given the background color) map to larger quantities. Previous work suggested that the background color only plays a role if visualizations appear to vary in opacity. The present study challenges this claim. We hypothesized that the background color modulate inferred mappings for colormaps that should not appear to vary in opacity (by previous measures) if the visualization appeared to have a "hole" that revealed the background behind the map (hole hypothesis). We found that spatial aspects of the map contributed to inferred mappings, though the effects were inconsistent with the hole hypothesis. Our work raises new questions about how spatial distributions of data influence color semantics in colormap data visualizations.

翻译：为创建有效的数据可视化，以直观方式利用视觉特征表示数据大有裨益。当可视化设计与观察者预期相符时，图表更易于解读。已有研究表明，多种因素会影响此类预期。例如，"深色即更多"偏差使观察者推断较深颜色对应较大数值，"不透明即更多"偏差则使其认为（在给定背景色下）不透明度更高的区域映射更大数值。先前工作认为，只有当可视化呈现透明度变化时，背景色才会产生影响。本研究对此论断提出质疑。我们假设：若可视化出现"孔洞"效应——即显示地图后方背景——则背景色可调节那些（按先前标准）不应呈现透明度变化的颜色映射的推断映射关系（孔洞假说）。研究发现，地图的空间特征会影响推断映射关系，但效应与孔洞假说不一致。本工作提出新问题：数据空间分布如何影响颜色映射图数据可视化中的色彩语义。