What Content Creators Need to Know About Data-Driven Journalism

Data and journalism have always been friends but in 2013, they are more like BFFs.

The word “data” is a little vague, but it’s the only way to describe the insane amount of information floating around the Web today. In the past few years, our eyes have been opened to the power of turning these raw numbers into stories, dollars and measurable results. 

Two people who have brought this topic into the public eye are Oakland Athletics general manager Billy Beane (yes, the Moneyball guy) and New York Times sabermetrician and writer Nate Silver. Both men proved that there is tangible value in data. They understood how to exploit it and helped spark a new era in sports, journalism, government, business and education.

OK, let’s back up a little bit. This post is about journalism. Newspapers have always used numbers to tell stories. Graphs, bars and charts are an excellent way to add context and perspective to a story. It’s a process that requires sharp editorial instincts, creative engineering and innovative collaboration between left- and right-brained individuals.

Journalists can bring data to life. What was once a spreadsheet can become the crux of a great story. At a recent Online News Association event, New York Times interactive news developer Derek Willis went into great detail about his experience using campaign finance data to create stories. He described the process as a constant back and forth between his editorial staff and their data team. It’s hard work for both parties, but it’s an investment in the reader and better content.

“This is a way to bring more ammunition to our side, to ask better questions, to tell better stories.” — @derekwillis on algorithms #onadc

— Jessica Estepa (@jmestepa) June 11, 2013

Data is more accessible now than ever, but it’s still a tough nut to crack for content teams. How do you find good data? How do you parse it? What does a data-driven story’s workflow look like?

The Guardian recently offered some insight into its own process, which could help other writers shape their own work.

Before a data set results in a data journalism story, there’s a whole process of sifting and finessing and generally sorting the data out. The split is roughly 70% tidying up the data, 30% doing the fun stuff of visualizing and presenting it. So, how do we get through that 70%?

Guardian graphic artist Mark McCormick has helped us visualize that process. So, yes, this is a graphic about how we produce data that often results in, er, graphics. A data visualization about data visualizations, if you will.

Click the image to download a PDF of this graphic.

Obviously, The New York Times and The Guardian have the budget and resources to invest heavily in data. Not every newsroom has that freedom, and most bloggers simply don’t have time to dig through huge data sets. But that doesn’t mean you should forget about using data in your content.

One easy way to start incorporating data into your content is to leverage surveys and studies in your vertical. If you write about government technology like I do, there is a wealth of free information available from the government as well as a number of independent organizations. Look for associations as well as vendors in your space for quality research.

Once you have the data, there are plenty of free tools to visualize it for your readers. Here are a few of my favorites:

• Infogr.am
• Piktochart
• Easel.ly
• Excel (sometimes, a simple graph is all you need.)

The Data Journalism Handbook is also an essential resource for editors and writers.

Do you have any resources for turning data into stories? Let us know in the comments.