While news outlets have used always used data to support their stories, in data journalism the data is actually the backbone of the story. Large data sets are analyzed and turned into something the reader can understand – anything from a short article to an interactive visualization.
For example, when The Texas Tribune wanted to tell a story about the impact of Food Stamps in the state of Texas, they used Texas State Government data to create a map showing the number of food stamps recipients by county.
Data Journalism often includes interactive elements that allow you to personalize the news story. In 2009, the Chicago Tribune published a story exposing elder abuse in retirement homes all over the state. Worried that your grandma could be suffering? The Chicago Tribune let you find out if there was cause for concern; the news story allowed readers to look up safety reports for every retirement home in the state of Illinois.
Sometimes the data in Data Journalism isn’t data in the strict numbers sense of the word, but news stories themselves. The Data Journalism project EveryBlock aggregates news stories, tweets, flickr photos and other social media posts, as well as crime reports, by area code, auto-generating a news feed for almost every block in America.
As governments and organizations release more and more data and the tools to analyze it become more and more user-friendly, data journalism will only grow in volume and importance. From American political watch-dogging to crowd-sourcing stories in Africa, everyone from large teams to individuals can have an impact.
If you’d like a peek into the world of Data Journalism, you should have a look at The Bastards Book of Ruby – an “an introduction to programming and its practical uses for journalists, researchers, scientists, analysts, and anyone else whose job is to seek out, make sense from, and show the hard-to-find data.” It’s plenty easy to read and understand and will have you on your way in no time!
Cocktail Party Fact
A developer named Adrian Holovaty is credited for writing the Data Journalism manifesto.
In this 2006 blog post, he argued that newspapers needed to think about news stories not as stories in and of themselves, but as an aggregation of a set of data points – the who, why, what, where, and when – that could be pulled apart and re-constituted to tell new and different stories.
Sounds great to us, but even five short years ago it was quite controversial!