Michael Burch
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.
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- The Power of Linked Eye Movement Data Visualizations
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