Paper accepted for AGILE 2018: Animation as a Visual Indicator of Positional Uncertainty in Geographic Information

We have a full paper accepted for AGILE 2018, which summarizes the results of our little online experiment about visualizations of uncertainty:

Here’s the preprint, and the abstract: Effectively communicating the uncertainty that is inherent in any kind of geographic information remains a challenge. This paper investigates the efficacy of animation as a visual variable to represent positional uncertainty in a web mapping context. More specifically, two different kinds of animation (a ‘bouncing’ and a ‘rubberband’ effect) have been compared to two static visual variables (symbol size and transparency), as well as different combinations of those variables in an online experiment with 163 participants. The participants’ task was to identify the most and least uncertain point objects in a series of web maps. The results indicate that the use of animation to represent uncertainty imposes a learning step on the participants, which is reflected in longer response times. However, once the participants got used to the animations, they were both more consistent and slightly faster in solving the tasks, especially when the animation was combined with a second visual variable. According to the test results, animation is also particularly well suited to represent positional uncertainty, as more participants interpreted the animated visualizations correctly, compared to the static visualizations using symbol size and transparency. Somewhat contradictory to those results, the participants showed a clear preference for those static visualizations.

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