Eye movements have a spatial (where people look), but also a temporal (when people look) component. Various types of visualizations have been proposed that take this spatio-temporal nature of the data into account, but it is unclear how well each one can be interpreted and whether such interpretation depends on the question asked about the data or the nature of the data-set that is being visualised. In this study, four spatio-temporal visualization techniques for eye movements (chord diagram, scanpath, scarfplot, space-time cube) were compared in a user study. Participants (N = 25) answered three questions (what region first, what region most, which regions most between) about each visualization, which was based on two types of data-sets (eye movements towards adverts, eye movements towards pairs of gambles). Accuracy of the answers depended on a combination of the data-set, the question that needed to answered, and the type of visualization. For most questions, the scanpath, which did not use area of interest (AOI) information, resulted in lower accuracy than the other graphs. This suggests that AOIs improve the information conveyed by graphs. No effects of experience with reading graphs (for work or not for work) or education on accuracy of the answer was found. The results therefore suggest that there is no single best visualisation of the spatio-temporal aspects of eye movements. When visualising eye movement data, a user study may therefore be beneficial to determine the optimal visualization of the data-set and research question at hand.

翻译：眼动具有空间（观看位置）和时间（观看时刻）双重维度。已有多种可视化方法考虑数据的时空特性，但各类方法的可解释性及其如何受数据查询需求、数据集特征的影响尚不明确。本研究通过用户实验对比了四种眼动时空可视化技术（弦图、扫描路径图、围巾图、时空立方体）。25名参与者基于两类数据集（广告眼动数据与赌博对眼动数据）完成每类可视化对应的三类任务（首个注视区域、最长注视区域、区域间转换频次）。结果显示，回答准确率取决于数据集、查询任务与可视化类型的交互作用。在多数任务中，未采用兴趣区（AOI）信息的扫描路径图准确率低于其他图表，表明兴趣区可增强图表信息传递效果。未发现图表阅读经验（职业需求与否）或教育背景对准确率的显著影响。研究结果表明，眼动时空特征不存在最优可视化方案。因此，在呈现眼动数据时，建议通过用户实验确定当前数据集与研究问题的最优可视化方案。