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What is an Interactive Data Visualization?

Interactive data visualizations are representations of information that allow the viewer to interact with
the data. As such, they’re in a different league from static
infographics
. They take programming to create, they usually have a lot more data, and they allow the
viewer to discover things on their own.

Interactive data visualizations allow users to explore a dataset for themselves -- often by providing details
on mouseover, giving different coordinated views, or panning and zooming. Unsurprisingly, some of the
best interactive data visualizations have been created by the Interactive or online departments of major
news organizations, and they tend to take advantage of modern web browsers.

For example, the CNN Ecosphere explores the potential
of WebGL with some beautiful results. The interactive data visualization is also live, pulling in current
Twitter data. You can use a hashtag or add your own tweet to the mix and see your opinion grow on a
tree.

Data Centric Universe shows just how far our
knowledge of our universe has come. There are only two time samples, but this works very well for the
interactive data visualization. The main story is to show the contrast between what we knew in 1950 and
what we know in 2011.

Data with many categories can be particularly good candidates for interactive data visualizations. Often
times the overlap and connections between the data cannot be conveyed through a static infographic.
Trends In Higher Education, for example, does a
great job of allowing the viewer to navigate many different categories and make sense of them all.

Data that change over time also benefit from interactivity.
Posted: US Growth Visualized Through Post Offices
uses a time range slider at the bottom of the infographic and is a great example of filtering in visualization.

An extremely interesting interactive data visualization focuses on the rumors that spread on Twitter
during the London riots of 2011. Riot Rumors does a fantastic
job of showing how these rumors were born, spread, and were corrected on one of the fastest social
networks around. Not only was the analysis done by the team great, but the interactive data visualization
calls out some pivotal events in the timeline of each rumor. As the timeline progresses, the main
visualization grows and changes like popcorn, showing the interaction of different rumor threads.

The effort involved in creating an interactive data visualizations is much higher, so many of them are very
good. Luckily, web-based data visualization tools
are making it easier to create
interactive data visualizations, but they still require effort -- especially when multiple datasets are
being compared.


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