Rind, A., Neubauer, B., Aigner, W., & Miksch, S. (2012). Static and Dynamic Visual Mappings to Explore Bivariate Data Across Time. In K. Matkovic & G. Santucci (Eds.), EuroVA 2012 Poster Proceedings (p. 3). http://hdl.handle.net/20.500.12708/54121
The 3rd International Eurovis workshop on Visual Analytics (EuroVA)
4-Jun-2012 - 5-Jun-2012
Number of Pages:
Time and time-oriented data are pivotal for many Visual Analytics scenarios. 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. 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, or by repetition (small multiples). Moreover, with small multiples either states or changes over time might be emphasized. To gather empirical evidence about the advantages and disadvantages of these different approaches, we developed a Visual Analytics prototype and conducted a comparative user study.
CVAST: Centre for Visual Analytics Science and Technology (Laura Bassi Centre of Expertise) HypoVis: Modeling Hypotheses with Visual Analytics Methods to Analyze the Past and Forecast the Future (Fonds zur Förderung der wissenschaftlichen Forschung (FWF))