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Eye tracking for visualization evaluation: Reading values on linear versus radial graphs

机译：眼动追踪以进行可视化评估：读取线性图和径向图上的值

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摘要

An eye tracking methodology can help uncover subtle cognitive processing stages that are otherwise difficult to observe in visualization evaluation studies. Pros and cons of eye tracking methods are discussed here, including common analysis metrics. One example metric is the initial time at which all elements of a visualization that are required to complete a task have been viewed. An illustrative eye tracking study was conducted to compare how radial and linear graphs support value lookup tasks for both one and two data-dimensions. Linear and radial versions of bar, line, area, and scatter graphs were presented to 32 participants, who each completed a counterbalanced series of tasks. Tasks were completed more quickly on linear graphs than on those with a radial layout. Scanpath analysis revealed that a three-stage processing model was supported: (1) find desired data dimension, (2) find its datapoint, and (3) map the datapoint to its value. Mapping a datapoint to its value was slower on radial than linear graphs, probably because eyes need to follow a circular, as opposed to a linear path. Finding a datapoint within a dimension was harder using line and area graphs than bar and scatter graphs, possibly due to visual confusion of the line representing a data series. Although few errors were made, eye tracking was also used here to classify error strategies. As a result of these analyses, guidelines are proposed for the design of radial and linear graphs.
机译：眼动追踪方法可以帮助发现细微的认知处理阶段，而这些阶段在可视化评估研究中很难观察到。本文讨论了眼动追踪方法的利弊，包括常见的分析指标。一个示例度量是初始时间，在该初始时间已查看了完成任务所需的可视化的所有元素。进行了说明性眼动追踪研究，以比较径向图和线性图如何支持一个和两个数据维的值查找任务。条形图，线形图，面积图和散点图的线性和径向版本分别向32位参与者展示，他们各自完成了一系列平衡任务。在线性图上完成任务比在径向布局上完成任务更快。扫描路径分析显示支持三阶段处理模型：（1）找到所需的数据维，（2）找到其数据点，（3）将数据点映射为其值。在径向上，将数据点映射为其值比在线性图上慢，这可能是因为眼睛需要遵循圆形而不是线性路径。使用线图和面积图要比条形图和散点图难找到一个维度内的数据点，这可能是由于代表数据序列的线的视觉混乱。尽管很少出错，但这里也使用眼动追踪对错误策略进行分类。这些分析的结果是，提出了设计径向图和线性图的准则。

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