The Power of Linked Eye Movement Data Visualizations

Michael Burch, Günter Wallner, Nick Broeks, Lulof Piree, N. Boonstra, Paul Vlaswinkel, Silke Franken, Vince van Wijk
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引用次数: 9

Abstract

In this paper we showcase several eye movement data visualizations and how they can be interactively linked to design a flexible visualization tool for eye movement data. The aim of this project is to create a user-friendly and easy accessible tool to interpret visual attention patterns and to facilitate data analysis for eye movement data. Hence, to increase accessibility and usability we provide a web-based solution. Users can upload their own eye movement data set and inspect it from several perspectives simultaneously. Insights can be shared and collaboratively be discussed with others. The currently available visualization techniques are a 2D density plot, a scanpath representation, a bee swarm, and a scarf plot, all supporting several standard interaction techniques. Moreover, due to the linking feature, users can select data in one visualization, and the same data points will be highlighted in all active visualizations for solving comparison tasks. The tool also provides functions that make it possible to upload both, private or public data sets, and can generate URLs to share the data and settings of customized visualizations. A user study showed that the tool is understandable and that providing linked customizable views is beneficial for analyzing eye movement data.
链接眼动数据可视化的力量
在本文中,我们展示了几个眼动数据可视化,以及如何将它们交互链接起来,以设计一个灵活的眼动数据可视化工具。该项目的目的是创建一个用户友好且易于访问的工具来解释视觉注意模式,并促进眼动数据的数据分析。因此,为了增加可访问性和可用性,我们提供了一个基于web的解决方案。用户可以上传自己的眼动数据集,并同时从多个角度进行检查。见解可以与他人共享和协作讨论。目前可用的可视化技术有二维密度图、扫描路径表示、蜂群图和围巾图,它们都支持几种标准的交互技术。此外,由于链接功能,用户可以在一个可视化中选择数据,并且相同的数据点将在所有活动的可视化中突出显示,以解决比较任务。该工具还提供了可以上传私有或公共数据集的功能,并可以生成url来共享自定义可视化的数据和设置。一项用户研究表明,该工具是可以理解的,提供链接的可定制视图有利于分析眼动数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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