cliques and bridges. Further, as with the
indented-tree layout, multivariate data
can easily be displayed alongside nodes.
The problem of sorting the nodes in a
manner that reveals underlying cluster
structure is formally called seriation and
has diverse applications in visualization, statistics, and even archaeology.
Matrix Views. Mathematicians and
computer scientists often think of a
graph in terms of its adjacency matrix:
each value in row i and column j in the
matrix corresponds to the link from
node i to node j. Given this representation, an obvious visualization then is:
just show the matrix! Using color or saturation instead of text allows values associated with the links to be perceived
The seriation problem applies just
as much to the matrix view, shown in
Figure 5c, as to the arc diagram, so
the order of rows and columns is important: here we use the groupings
generated by a community-detection
algorithm to order the display. While
path-following is more difficult in a
matrix view than in a node-link diagram, matrices have a number of compensating advantages. As networks
get large and highly connected, node-link diagrams often devolve into giant
hairballs of line crossings. In matrix
views, however, line crossings are impossible, and with an effective sorting one quickly can spot clusters and
bridges. Allowing interactive grouping and reordering of the matrix facilitates even deeper exploration of network structure.
We have arrived at the end of our tour
and hope the reader has found the examples both intriguing and practical.
Though we have visited a number of
visual encoding and interaction techniques, many more species of visualization exist in the wild, and others await
discovery. Emerging domains such as
bioinformatics and text visualization
are driving researchers and designers to
continually formulate new and creative
representations or find more powerful
ways to apply the classics. In either case,
the DNA underlying all visualizations
remains the same: the principled mapping of data variables to visual features
such as position, size, shape, and color.
As you leave the zoo and head back
share a common
“Dna”—a set of
data properties and
such as position,
might always be
into the wild, try deconstructing the
various visualizations crossing your
path. Perhaps you can design a more effective display?
Now I See It: Simple Visualization
Techniques for Quantitative Analysis.
Analytics Press, 2009.
The Visual Display of Quantitative
Information. Graphics Press, 1983.
Envisioning Information. Graphics Press,
Visual Thinking for Design. Morgan
The Grammar of Graphics. Springer, 1999.
Visualization Development Tools
Prefuse: Java API for information
Prefuse Flare: ActionScript 3 library for data
visualization in the Adobe Flash Player.
Processing: Popular language and IDE for
graphics and interaction.
The Visualization Toolkit: Library for 3D
and scientific visualization.
A Conversation with Jeff heer, Martin
Wattenberg, and Fernanda Viégas
Unifying Biological Image Formats
Matthew T. Dougherty, Michael J. Folk,
Erez Zadok, Herbert J. Bernstein,
Frances C. Bernstein, Kevin W. Eliceiri,
Werner Benger, Christoph Best
Jeffrey heer is an assistant professor of computer
science at Stanford university, where he works on human-computer interaction, visualization, and social computing.
He led the design of the Prefuse, Flare, and Protovis
Michael Bostock is currently a Ph. D. student in the
Department of Computer Science at Stanford university.
before attending Stanford, he was a staff engineer at
google, where he developed search quality evaluation
Vadim Ogievetsky is a master’s student at Stanford
university specializing in human-computer interaction.
He is a core contributor to Protovis, an open-source Web-based visualization toolkit.