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Many of the examples in this topic discuss how to deal with the challenges of very
large datasets. Relatively new open-source technologies, including nonrelational data-
bases and distributed processing frameworks such as Hadoop, have made collecting and
processing large amounts of data more accessible than ever. The ability of humans to
comprehend large amounts of spatial data, however, has not evolved accordingly.
Interactivity
Before the invention of the digital display, charts were bound to paper. Thankfully,
visualizations are no longer shackled to a static substrate. Over the past few decades,
the development of new interfaces has increased the speed with which researchers have
developed innovative visualization techniques. Using methodology borrowed from
the world of user experience and cognitive science, data visualization researchers are
increasingly able to quantify the effectiveness of their work. As a result, new types
of visual data representations are being developed all the time. An example of fairly
recent visualization innovation includes the
Streamgraph
,
6
a comparative, f lowing
area graph developed as an improved way to compare large, changing datasets over
time. Similarly, Edward Tufte's
Sparklines
visualization
7
concept (developed in the
late 1990s) embedded short, intense line-graph metrics of a single changing metric
within surrounding text. This type of visualization has become a common feature of
online financial publications.
Interactive visualizations enable researchers with very large, multifaceted datasets
to allow end users to select the slices of data that are relevant for answering a particu-
lar data question. A well-known example of online, interactive visualizations is the
pioneering work of Hans Rosling who, through his Gapminder Foundation, led the
development of a software tool known as Trendalyzer. Trendalyzer enables users to
compare a variety of economic metrics of the countries of the world (such as aver-
age income and birth weight) through a
bubble chart
visualization. Along with this
representation, the tool adds an element of time, giving users the ability to play back
changes in country metrics as they change over time.
In summary, interactive visualizations provide yet another strategy for providing
visual representations of large datasets. By allowing users to select facets of the data to
explore, it's sometimes possible to reduce the worrisome problems of clutter and visual
overload that can render visualizations useless.
6. Byron, Lee, and Martin Wattenberg. “Stacked Graphs—Geometry & Aesthetics.”
IEEE
Transactions on Visualization and Computer Graphics
14, no. 6 (November/December 2008):
1245-1252.
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