Abstract
The research focused on use of animations to visually explore geodata. Evidence about the usefulness of animations is mixed: animations better display the micro steps between important changes than static displays, but they may also be overwhelming and ‘change blindness’ may occur. Is it possible to extract useful information from
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an animation if application and design are carefully considered? This question underlied the research. Vegetation monitoring was used as case study: monitoring is about keeping track of change and even minor changes can be important. The research was limited to variables of the temporal dimension of animations: the dynamic visualization variables moment of display, order, duration and frequency. Developing methods by which these variables can be used to acquire information from imagery was a main objective. Since little is known about actual use of animations of geodata, another main objective was to gain knowledge of cognitive processes and strategies applied by domain experts while working with a prototype.
Literature review and interviews with domain experts gave insight into aspects of change that are important for monitoring and in the main monitoring objectives and questions. Next, investigation into characteristics of change that can be visually perceived in an animation led to generic concepts, describing characteristics that should trigger relevant domain knowledge. Investigation into the dynamic visualization variables focused on ways to use these variables to represent geodata and to control the animation by interaction. Interaction is important to enable visual exploration, but also to (at least partly) overcome change blindness. Hypothetical effects of the variables on users were described and predictions were made on how users would apply them in a task with the prototype.
A first version of the prototype was slightly adjusted after a focus group session. Detailed evaluation of aNimVis by domain experts followed. Data were gathered from ten participants who were thinking aloud during execution of a task, consisting of some typical monitoring questions. Additional data were gathered in post-test interviews and a questionnaire.
Verbal and action protocols, generated from integrated video recordings of the ‘problem-solving behaviour’ of participants, were analysed in various ways. Main problem solving phases were distinguished. Analysis of the (relative) importance of animation tools gave remarkable results for the ‘tuning’ option. Differences in tool use and reasoning among participants revealed main animation use strategies. Predictions about tool and effect use were compared to actual use. Although deviations occurred, the relative importance of effects and relations to tasks could be established. These links between effects and tasks can be extended to improve the theoretical framework for application of the dynamic visualization variables. All users were able to extract relevant information from the animation. User feedback revealed problems, usability ratings and desired extensions of the prototype. All participants would like to use aNimVis to explore and analyze data if it was linked to GIS or image processing software. Finally, recommendations to make animations more effective and for further research are given.
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