Interactive data visualization

Part of a series on Statistics
Data visualization
Major dimensions Exploratory data analysis • Information design Interactive data visualization Descriptive statistics • Inferential statistics Statistical graphics • Plot Data analysis  • Infographic Data science
Thought leaders Tamara Munzner  • Ben Shneiderman  • John W. Tukey  • Edward Tufte  • Fernanda Viégas  • Hadley Wickham
Information graphic types Line chart  • Bar chart Histogram • Scatterplot Boxplot • Pareto chart Pie chart • Area chart Control chart  • Run chart Stem-and-leaf display • Cartogram Small multiple • Sparkline Table
Related Topics Data • Information Big data • Database Chartjunk • Visual perception Regression analysis • Statistical model Misleading graph

interactive data visualization enables direct actions on a plot to change elements and link between multiple plots.^[1]

Overview

Interactive data visualization has been a pursuit of statisticians since the late 1960s. Examples of the developments can be found on the ASA video lending library.^[2]

Common interactions

• Brushing: works by using the mouse to control a paintbrush, directly changing the color or glyph of elements of a plot. The paintbrush is sometimes a pointer and sometimes works by drawing an outline of sorts around points; the outline is sometimes irregularly shaped, like a lasso. Brushing is most commonly used when multiple plots are visible and some linking mechanism exists between the plots. There are several different conceptual models for brushing and a number of common linking mechanisms. Brushing scatterplots can be a transient operation, in which points in the active plot only retain their new characteristics while they are enclosed or intersected by the brush, or it can be a persistent operation, so that points retain their new appearance after the brush has been moved away. Transient brushing is usually chosen for linked brushing, as we have just described.
• Painting: Persistent brushing is useful when we want to group the points into clusters and then proceed to use other operations, such as the tour, to compare the groups. It is becoming common terminology to call the persistent operation painting,
• Identification: which could also be called labeling or label brushing,is another plot manipulation that can be linked. Bringing the cursor near a point or edge in a scatterplot, or a bar in a barchart, causes a label to appear that identifies the plot element. It is widely available in many interactive graphics, and is sometimes called mouseover.
• Scaling: maps the data onto the window, and changes in that mapping function help us learn different things from the same plot. Scaling is commonly used to zoom in on crowded regions of a scatterplot, and it can also be used to change the aspect ratio of a plot, to reveal different features of the data.
• Linking: connects elements selected in one plot with elements in another plot. The simplest kind of linking, one-to-one, where both plots show different projections of the same data, and a point in one plot corresponds to exactly one point in the other. When using area plots, brushing any part of an area has the same effect as brushing it all and is equivalent to selecting all cases in the corresponding category. Even when some plot elements represent more than one case, the underlying linking rule still links one case in one plot to the same case in other plots. Linking can also be by categorical variable, such as by a subject id, so that all data values corresponding to that subject are highlighted, in all the visible plots.

See also

• Comparison of JavaScript charting frameworks

References