Comparison of Temporally Classified and Unclassified Map Animations

While animation is a natural and, under certain circumstances, effective way to present spatio-temporal information, it has its limitations. Studying animations of large point datasets can be cognitively very demanding. Aiming to help users to comprehend such data, this study presents a new concept of temporal classification. A phenomenon is classified into periods of increasing, decreasing, and steady intensity, and each is assigned different colours in an animation. This concept was tested with a group of experts in the field of the phenomenon. The results suggest that this kind of classified animation, together with a traditional animation presenting the same dataset, supports users in their analysis process and adds to the impression they get of the phenomenon. It also seems that the viewing order of the animations matters: the full potential of the tested method is reached by viewing the traditional version first and temporally classified version after that.