There are multiple barriers that data journalists face. Stephen Doig, Pulitzer Prize -winning data journalist from Arizona State University, says that not getting information from officials even when it is public is one of the key barriers.
“Despite the US laws, that permit to have certain information, we often have to go to court to fight for these rights,” he says.
Another barrier is the complexity of topics. Journalists typically have not spent their entire careers familiarizing in certain topics. Also data analyzing skills have been picked through practice.
Some of the biggest newspapers have employed talented people from the computer science world to do data visualizations, but the analysis side of data journalism is usually done by journalists.
However, to Doig’s experience it is easier to train a journalist to learn how to work with data than take a data scientist and teach journalism.
Also time builds pressure. At least smaller papers don’t have staff to put aside to work on time-consuming data journalism projects.
Text is one barrier: Figures are reasonably easy to convert into graphics etc., but when newspapers get vast amounts of text, it is still a big battle to go through the material and get a story out of it. He gives WikiLeaks as an example of having to read massive amounts of text, word by word.
Doig wonders why authorities aren’t always doing their own data analysis.
“Government agencies from which journalists get their info, should be doing the same thing themselves,” Doig argues.