Department of Computer Science, University of Illinois at Chicago, USA.
IEEE Trans Vis Comput Graph. 2010 Nov-Dec;16(6):1044-52. doi: 10.1109/TVCG.2010.197.
An ongoing challenge for information visualization is how to deal with over-plotting forced by ties or the relatively limited visual field of display devices. A popular solution is to represent local data density with area (bubble plots, treemaps), color (heatmaps), or aggregation (histograms, kernel densities, pixel displays). All of these methods have at least one of three deficiencies:1) magnitude judgments are biased because area and color have convex downward perceptual functions, 2) area, hue, and brightness have relatively restricted ranges of perceptual intensity compared to length representations, and/or 3) it is difficult to brush or link to individual cases when viewing aggregations. In this paper, we introduce a new technique for visualizing and interacting with datasets that preserves density information by stacking overlapping cases. The overlapping data can be points or lines or other geometric elements, depending on the type of plot. We show real-dataset applications of this stacking paradigm and compare them to other techniques that deal with over-plotting in high-dimensional displays.
信息可视化的一个持续挑战是如何处理由关联或显示设备相对有限的视场引起的过度绘制。一种流行的解决方案是使用面积（气泡图、树图）、颜色（热图）或聚合（直方图、核密度估计、像素显示）来表示局部数据密度。所有这些方法都至少存在以下三个缺陷之一：1）由于面积和颜色具有向下凸的感知功能，因此幅度判断存在偏差，2）与长度表示相比，面积、色调和亮度的感知强度范围相对受限，和/或 3）在查看聚合时，很难进行刷选或链接到单个案例。在本文中，我们介绍了一种新的技术，用于通过堆叠重叠案例来可视化和交互处理数据集，保留密度信息。重叠的数据可以是点、线或其他几何元素，具体取决于图形的类型。我们展示了这种堆叠范例的实际数据集应用，并将其与其他处理高维显示中超图的技术进行了比较。
