Towards location-aware mobile eye tracking
Proceedings of the Symposium on Eye Tracking Research and Applications
Gaze map matching: mapping eye tracking data to geographic vector features
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
The influence of gaze history visualization on map interaction sequences and cognitive maps
Proceedings of the 1st ACM SIGSPATIAL International Workshop on MapInteraction
AOI rivers for visualizing dynamic eye gaze frequencies
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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Visual analytics is often based on the intuition that highly interactive and dynamic depictions of complex and multivariate databases amplify human capabilities for inference and decision-making, as they facilitate cognitive tasks such as pattern recognition, association, and analytical reasoning (Thomas and Cook 2005). But how do we know whether visual analytics really works? This article offers a generic evaluation approach combining theory-and data-driven methods based on sequence similarity analysis. The approach systematically studies users' visual interaction strategies when using highly interactive interfaces. We specifically ask whether the efficiency (i.e., speed) of users can be characterized by specific display interaction event sequences, and whether studying user strategies could be employed to improve the (interaction) design of the dynamic displays. We showcase our approach using a very large, fine-grained spatiotemporal dataset of eye movement recordings collected during a controlled human subject experiment with dynamic visual analytics displays. With this methodological approach based on empirical evidence, we hope to contribute to a deeper understanding of how people make inferences and decisions with highly interactive visualization tools and complex displays.