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The art of numbers: Who knew Big Data could look so cool?

Narasu Rebbapragada | Sept. 19, 2013
Bold graphics tell a human story that spreadsheets cannot.

A bright orange line emerges from the horizon at the left side of the screen. Getting brighter, it arcs upward--and then suddenly turns ashen gray before falling back to the horizon. More lines follow the first. Thousands upon thousands of lines. The visual is at once beautiful and daunting.

That's because the lines aren't merely lines. Each one represents the life of an American who was suddenly and violently snuffed out by gunfire. Each one is just a statistic in a database, but the "socially conscious" data visualization firm Periscopic brought the numbers to life in a dramatic illustration that makes a powerful statement: Some 7500 people have been killed by guns so far in 2013 (the orange lines), and those victims lost a projected 330,000-plus total years of life, liberty, and the pursuit of happiness (the gray lines).

Such is the power of the data visualization, a unique blend of graphic art and data science that's helping both researchers and everyday people make sense of the ever-growing databases that increasingly influence our lives.

When done well (as in Periscopic's gun-death example), data visualizations can express the meanings hidden in massive data sets in an immediate and intuitive way. "I was shocked. I realized the scale I was looking at, and then I saw the volume," says Periscopic cofounder Dino Citraro. "It scared me."

Helping Big Data 'speak'
Of course, infographics are nothing new. People have made careers out of visualizing data since William Playfair created his first charts and graphics in the 18th century, and since Edward Tufte popularized modern information graphics in the 1980s. But today's data visualizations wrangle much more information, and they're far more sophisticated in their use of multimedia graphics and computer engineering platforms.

Big Data is helping to fuel the revolution. Governments, corporations, and individuals are collecting more and more data about people, behaviors, demographics, habits, and preferences. All this information comes from a multitude of sources, including satellites, wearable fitness devices, surveillance cameras, the Internet, cell networks, and social media. A new NSA data warehouse, opening soon in Utah, will store exabytes of surveillance data, for example. (An exabyte is roughly 1 billion gigabytes.)

Databases in both the public and private sectors are growing so big and multidimensional that perceiving patterns and trends within them is becoming a huge challenge. Enter the new breed of visualizations, which make it much easier to see patterns and trends that would otherwise be hidden inside giant spreadsheets. They can also express big-picture messages that raw numbers can't easily explain.

The process of making visualizations varies, but generally it starts with the collection of raw data, which the visualization creators then analyze and model to tease out initial shapes and patterns. The creators can use a variety of tools for this task, such as the commercial business platform Tableau, free statistical software such as R, and the open-source package Processing. Artists then bring the visuals to life, with the help of Adobe design software and even movie-industry tools such as Autodesk Maya. Finally, the visualization is coded, rendered, and served up on websites and apps for viewing on a PC or tablet.

 

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