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FeaturEyeTrack: automatic matching of eye tracking data with map features on interactive maps

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Abstract

Map reading is a visual task that can strongly vary between individuals and maps of different characteristics. Aspects such as where, when, how long, and in which sequence information on a map is looked at can reveal valuable insights for both the map design process and to better understand cognitive processes of the map user. Contrary to static maps, for which many eye tracking studies are reported in the literature, established methods for tracking and analyzing visual attention on interactive maps are yet missing. In this paper, we present a framework called FeaturEyeTrack that allows to automatically log the cartographic features that have been inspected as well as the mouse input during the interaction with digital interactive maps. In particular, the novelty of FeaturEyeTrack lies in matching of gaze with the vector model of the current map visualization, therefore enabling a very detailed analysis without the requirement for manual annotation. Furthermore, we demonstrate the benefits of this approach in terms of manual work, level of detail and validity compared to state-of-the-art methods through a case study on an interactive cartographic web map.

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  • 02 May 2019

    The original version of this article unfortunately contained a mistake. Figure 10a and b were interchanged during the publishing process.

Notes

  1. A preliminary version of this framework was presented as a short paper at the AGILE Conference in 2017 [29].

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Acknowledgements

This work is supported by the Swiss National Science Foundation under Grant No.: 200021_162886.

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  1. ETH Zurich, Institute of Cartography and Geoinformation, CH-8093, Zurich, Switzerland

    Fabian Göbel, Peter Kiefer & Martin Raubal

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  1. Fabian Göbel
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Correspondence to Fabian Göbel.

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The ​original ​version ​of ​this ​article ​was ​revised: Figure 10a and b were interchanged during the publishing process.

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Göbel, F., Kiefer, P. & Raubal, M. FeaturEyeTrack: automatic matching of eye tracking data with map features on interactive maps. Geoinformatica 23, 663–687 (2019). https://doi.org/10.1007/s10707-019-00344-3

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