Digging into data journalism

What is the role of data journalism today? How has it evolved?

Data journalism has evolved from a rarefied skill set that only computer-assisted reporters practiced to become an important tool in the toolkit of every journalist. That’s not to say that every reporter needs to know how to code, but every reporter does need to be able to read a spreadsheet and have basic quantitative understanding. We need these skills because the agencies and companies we cover communicate in the language of data. If journalists can’t draw their own conclusions from the data, then they’re left simply accepting at face value the findings of the people they cover. It would be like a photographer using only handout photos.

How did the Stylebook editors decide what to include in this new chapter?

This is a set of guidelines for doing data journalism and not intended to be a complete course in the topic. Like the rest of the Stylebook, this section is designed to highlight potentially confusing or troublesome issues and to provide clarity about AP standards.

We tried to cover important questions in each stage of the data reporting process, and we tried to tackle some of the more vexing questions, such as the proper handling of leaked data, the ethics of web scraping and standards for accurately representing data findings in text and visuals. But we know there’s a lot more to say. We’re looking forward to feedback about what would be useful for future editions and for supplementary content we can publish to the online Stylebook.

Part of the chapter focuses on reproducible analysis – the equivalent of showing your work. What does that mean for news organizations large and small?

Providing readers with a roadmap to replicate the analysis we’ve done is an essential element of transparency in our reporting. We can accomplish this transparency in many ways, depending on the data set and the story. Many news organizations are publishing the code and data behind the analysis along with the story. At AP, we’re providing the data and documentation behind our work to our member news organizations, so that they can find the story in the data most relevant to their audience.

But even data journalists who don’t write code can provide sufficient information in a methodology statement or “nerd box” so that other journalists or interested readers could follow in their footsteps and verify the findings. “Show your work” has become a bit of a truism in data journalism over the years, but it’s a core value. Just as we wouldn’t want to simply trust a government agency to do our analysis for us, we can’t simply ask our readers to trust that we’ve gotten the analysis right without showing them how we arrived at our findings.