Deborah Swayne, Duncan Temple Lang, and Andreas Buja (2003), Visual Exploration of Graph Data, Computing Science and Statistics, 35, I2003Proceedings/SwayneDeborah/SwayneDeborah.presentation.pdf
Graphs have long been of interest in telecommunications and social network analysis, and they are now receiving increasing attention from statisticians working in other areas, particularly in biostatistics.
Most of the visualization software available for working with graphs has come from outside statistics and has not included the kind of interaction that statisticians have come to expect. At the same time, most of the exploratory visualization software available to statisticians has made no provision for the special structure of graphs.
Graphics software for the exploratory visual analysis of graph data should include the following: graph layout methods; a variety of displays and methods for exploring variables on both nodes and edges, including methods that allow these covariate displays to be linked to the network view; methods for thinning a dense graph. In addition, the power of the visualization software is greater if it can be smoothly linked to an extensible and interactive statistics environment.
In this talk, we'll describe and demonstrate how these goals have been addressed in GGobi through its data format, graphical user interface design, and its relationship to the R software.