University of Konstanz.
Inria.
IEEE Trans Vis Comput Graph. 2014 Dec;20(12):2251-2260. doi: 10.1109/TVCG.2014.2346426.
We conducted three experiments to investigate the effects of contours on the detection of data similarity with star glyph variations. A star glyph is a small, compact, data graphic that represents a multi-dimensional data point. Star glyphs are often used in small-multiple settings, to represent data points in tables, on maps, or as overlays on other types of data graphics. In these settings, an important task is the visual comparison of the data points encoded in the star glyph, for example to find other similar data points or outliers. We hypothesized that for data comparisons, the overall shape of a star glyph--enhanced through contour lines--would aid the viewer in making accurate similarity judgments. To test this hypothesis, we conducted three experiments. In our first experiment, we explored how the use of contours influenced how visualization experts and trained novices chose glyphs with similar data values. Our results showed that glyphs without contours make the detection of data similarity easier. Given these results, we conducted a second study to understand intuitive notions of similarity. Star glyphs without contours most intuitively supported the detection of data similarity. In a third experiment, we tested the effect of star glyph reference structures (i.e., tickmarks and gridlines) on the detection of similarity. Surprisingly, our results show that adding reference structures does improve the correctness of similarity judgments for star glyphs with contours, but not for the standard star glyph. As a result of these experiments, we conclude that the simple star glyph without contours performs best under several criteria, reinforcing its practice and popularity in the literature. Contours seem to enhance the detection of other types of similarity, e. g., shape similarity and are distracting when data similarity has to be judged. Based on these findings we provide design considerations regarding the use of contours and reference structures on star glyphs.
我们进行了三项实验,旨在研究轮廓线对星型象形图变化数据相似性检测的影响。星型象形图是一种小型紧凑的数据图形,用于表示多维数据点。星型象形图常用于小倍数设置中,用于表示表格中的数据点、地图上的数据点或作为其他类型数据图形的覆盖层。在这些设置中,一个重要的任务是可视化比较星型象形图中编码的数据点,例如,找到其他相似的数据点或异常值。我们假设,对于数据比较,星型象形图的整体形状(通过轮廓线增强)将有助于观察者做出准确的相似性判断。为了验证这一假设,我们进行了三项实验。在我们的第一项实验中,我们探讨了轮廓线的使用如何影响可视化专家和训练有素的新手选择具有相似数据值的象形图。我们的结果表明,没有轮廓线的象形图使得数据相似性的检测更加容易。基于这些结果,我们进行了第二项研究以了解相似性的直观概念。没有轮廓线的星型象形图最直观地支持数据相似性的检测。在第三个实验中,我们测试了星型象形图参考结构(即刻度线和网格线)对相似性检测的影响。令人惊讶的是,我们的结果表明,添加参考结构确实可以提高具有轮廓线的星型象形图相似性判断的正确性,但对标准星型象形图没有影响。通过这些实验,我们得出结论,在几个标准下,没有轮廓线的简单星型象形图表现最佳,这加强了它在文献中的实践和普及。轮廓线似乎增强了对其他类型相似性的检测,例如形状相似性,而在需要判断数据相似性时则会分散注意力。基于这些发现,我们提供了有关在星型象形图上使用轮廓线和参考结构的设计注意事项。