Effectiveness of Animation in Trend Visualization

Abstract

Abstract-Animation has been used to show trends in multi-dimensional data. This technique has recently gained new prominence for presentations, most notably with Gapminder Trendalyzer. In Trendalyzer, animation together with interesting data and an engaging presenter helps the audience understand the results of an analysis of the data. It is less clear whether trend animation is effective for analysis. This paper proposes two alternative trend visualizations that use static depictions of trends: one which shows traces of all trends overlaid simultaneously in one display and a second that uses a small multiples display to show the trend traces side-by-side. The paper evaluates the three visualizations for both analysis and presentation. Results indicate that trend animation can be challenging to use even for presentations; while it is the fastest technique for presentation and participants find it enjoyable and exciting, it does lead to many participant errors. Animation is the least effective form for analysis; both static depictions of trends are significantly faster than animation, and the small multiples display is more accurate.Index Terms-Information visualization, animation, trends, design, experiment. INTRODUCTION: TREND VISUALIZATIONInformally, the term trend means to have a general tendency (Webster's Dictionary). A trend in data is an observed general tendency. The most common way to see a trend in data is to plot a variable's change over time on a line chart or bar chart. If there is a general increase or decrease over time, this is perceived as a trend up or down. If there is a general increase/decrease that reverses direction, it is perceived as a reversing trend (for up to a few reversals). If there are more than a few reversals, it appears to be cyclic or noisy data, and no trend is perceived. Plotting multiple variables on a timeline (as in a multiple line chart) sometimes allows the user to see counter-trends. For example, if most of the variables are generally increasing and a few are decreasing, the decreasing variables can pop out and be perceived as counter-trends. If there is not much variation for any variable, it is possible to fit a regression line or curve and plot it as a trend line or trend curve. More formally, trend estimation is a statistical technique for identifying these trend lines or trend curves [5]. For purposes of discussion in this paper, we will focus only on informal trends that can be perceived visually without statistical trend estimation.The simple approach described above only works for a number of variables along one dimension plotted against another dimension (usually time). What is the best way to see trends in two or three dimensions simultaneously?Gapminder Trendalyzer [8] is an animated bubble chart designed to show trends over time in three dimensions. Both the size and locations of bubbles smoothly animate as time passes. This technique appears to be very effective in presentations, where a presenter tells the observer where to focus attention. It makes the ...

Temporal Multivariate Networks

“…Applications of this framework include visualizing software evolution [24], social networks analysis [9], and the behavior of dynamically modifiable code [30]. Robertson et al [89] evaluate the effectiveness of three trend visualization techniques. The results indicate that animation, often enjoyable and exciting, is not always well suited to data analysis.…”

Visual Detection of Change Points and Trends Using Animated Bubble Charts

“…However, as emphasized in the introduction, only a few different colours and bubble sizes can be readily distinguished by visual inspection, and there may be perceptual interference between colour and size coding (Healey, 2000;Bartram, 2001). In addition, it should be mentioned that static visualizations, such as a small multiples display, are still viable alternatives to animated graphs (Robertson et al, 2008). Much of the work presented here was inspired by Rosling and co-workers (Gapminder, 2011), who demonstrated that the animated bubble chart is a powerful tool for visualizing temporal trends in official statistics and other data collected annually for a set of objects.…”

“…The use of animated population pyramids in official statistics (the Australian Bureau of Statistics, 2011) illustrates that almost any static graph in statistics can be animated to visualize changes over time. However, some authors have emphasized that animations are not always superior to static presentations such as a small multiples display (Robertson et al, 2008). Visualization of temporal changes in the size and shape of 2D point clouds represents yet another approach that is particularly suitable for exploring large datasets (Landesberger et al, 2009).…”

Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data

“…Visualizing trends in time-varying and multi-variate data has been considered in depth within the information visualization community [6]. However, for visualization of biomechanical motion over time, 3D views of the model are often animated, and additional data attributes are often visualized using color, texture, streamlines, and 3D data glyphs [2,7,8].…”

“…However, for visualization of biomechanical motion over time, 3D views of the model are often animated, and additional data attributes are often visualized using color, texture, streamlines, and 3D data glyphs [2,7,8]. While these annotated 3D views can be quite powerful, it has been suggested that understanding trends over time through animation may not be the most effective strategy [6]. Our system follows the framework developed by Keefe et al [3] in that we also utilize a multiple coordinated visualization approach and support analysis using both the 3D model view and 2D information visualizations.…”