If a picture is worth a thousand words, a viral infographic is worth 10,000 page views. But many companies are still behind the data visualization curve because of perceived barriers of entry—the notion that only computer whizzes, database hounds and stat geeks with a flair for graphic design can produce compelling infographics. But new tools and software are effectively imploding those barriers and making data visualization more accessible to the masses.
One of the most important new guides to DIY data design is The Data Journalism Handbook. The first of its kind, the handbook is an open-source, seven-part compendium that outlines best practices for collecting, analyzing and finally presenting data in an engaging visual form. The Handbook also provides real-world case studies, step-by-step examples and a variety of perspectives by different authors. The information is presented in a format accessible to newcomers, but even veterans of data visualization will find useful tips and tricks. Plus, the open-source version online is free.
Though it’s tailored to journalists, a lot of the information is applicable to anyone interested in collating and graphically representing information. After all, reporting is little more than compiling information and then using it to tell a story. Many companies already do this, either for internal or external communications, or for their own management purposes.
The editors of the handbook are Jonathan Gray, Liliana Bounegru and Lucy Chambers, who work for the Open Knowledge Foundation in the UK—a sort of think tank for open source information. In a blog post about the handbook, Gray called it a “collaborative effort involving dozens of data journalism’s leading advocates and best practitioners.”
Stephen Doig, a Pulitzer Prize winning journalist and Arizona State professor specializing in computer-assisted journalism, was one of the many contributors to the handbook.
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Doig noted that one reason the handbook is important to journalists is because their field is often leading the way in data visualization. Although the skill set is applicable to a wide range of industries, many companies keep their communications and data internal and have less incentive to present the information to the public.
But the ability to build graphical databases or interactive charts has a broad appeal because it puts the information into the hands of the user. “This ability gives us the opportunity for readers to go beyond what we tell them and explore the information themselves,” he said.
There are also tools available that can assist novices with taking data and turning it into something that’s understandable and visual. In the past, data visualization has required advanced skills in information management and graphic design. Today, desktop applications can make it easier for the layperson to build charts, graphs and scatter plots without having to rely on proprietary programs—or worse yet build their own.
Tableau is perhaps the best example. Considered the “Excel for millennials,” the program allows users to drag and drop various datasets to create real-time visualizations. Excel files can be dropped directly into Tableau to create graphical representations of the information. Doig also points to other easy-to-use programs such as Ruby on Rails and Django that also allow users to rather easily manage and present data.
Geoff McGhee, another contributor to the handbook, is also an academic and Pulitzer Prize winner. A communications professor at Stanford University, McGhee produced a video report on data visualization a couple of years back that got him noticed by the editors of the Data Journalism Handbook.
McGhee’s interest in data visualization stems from what he sees as a changing landscape for storytelling and the ease with which people can now present very specific data visually, including variable arch data sets.
“Virtually every discipline is grappling with the fact that they are coming into contact with vast amounts of data” he said.
In the past, this deluge of information was overwhelming, and many companies lacked servers large enough to process such large files in graphic form. But McGhee argues that data visualization has become more popular and accessible in recent years because of the Amazon Elastic Compute Cloud, which provides extra capacity. Complicated visualizations no longer crash systems.
The Data Journalism Handbook is one handy resource, also providing a blueprint for transforming these large data sets into engaging graphics readers and consumers can wrap their heads around.
Know of any other instructional resources for data visualization? Let us know in the comments section.