Static and Dynamic Visual Mappings to Explore Bivariate Data Across Time

Time and time-oriented data are pivotal for many Visual Analytics scenarios [AMST11]. In principle, the time dimension can be represented using the display space (static mapping, e.g., line plot) or physical time (dynamic mapping, e.g., animation). Dynamic mapping is more direct and, thus, a promising visual metaphor. However, there are contradicting results on its effectiveness for analytical reasoning [RFF∗08]. To explore the mutual behavior of two variables, the most popular visual method is probably the scatter plot. However, an individual scatter plot is only a static snapshot of the relationship of two variables and developments over time cannot be seen. Hence, time can be added either using an animated scatter plot [RAM∗11], or by repetition (small multiples [Tuf83]). Moreover, with small multiples either states or changes over time might be emphasized.