State change comparison of multiple data items is often necessary in multiple application domains, such as medical science, financial engineering, sociology, biological science, etc. Slope graphs and grouped bar charts have been widely used to show a "before-and-after" story of different data states and indicate their changes. However, they visualize state changes as either slope or difference of bars, which has been proved less effective for quantitative comparison. Also, both visual designs suffer from visual clutter issues with an increasing number of data items. In this paper, we propose Intercept Graph, a novel visual design to facilitate effective interactive comparison of state changes. Specifically, a radial design is proposed to visualize the starting and ending states of each data item and the line segment length explicitly encodes the "state change". By interactively adjusting the radius of the inner circular axis, Intercept Graph can smoothly filter the large state changes and magnify the difference between similar state changes, mitigating the visual clutter issues and enhancing the effective comparison of state changes. We conducted a case study through comparing Intercept Graph with slope graphs and grouped bar charts on real datasets to demonstrate the effectiveness of Intercept Graph.
翻译:在许多应用领域,如医学、金融工程、社会学、生物科学等,往往有必要对多种数据项目进行国家变化比较。 坡形图和组合条形图被广泛用来显示不同数据状态的“前后”故事,并显示其变化。然而,它们将状态变化想象成斜坡或条形差异,这已证明对定量比较来说不太有效。此外,两种视觉设计都存在视觉模糊问题,数据项目越来越多。在本文件中,我们提出截图,这是便利有效交互比较国家变化的新型视觉设计。具体地说,我们建议用一个线形设计,将每个数据项目的起始和结束状态和线形线条长度直观化为“状态变化”编码。通过交互调整内圆轴的半径,截图可以顺利地过滤较大的状态变化,放大相似的状态变化之间的差别,减轻视觉模糊问题,并加强对状态变化的有效比较。我们通过将截面图与斜面图和真实数据图上的分组条形图进行比较,进行了案例研究。