Over the past year, an important element of my research into data journalism’s past, present and future has been interviews with young journalists like Jeremy Bowers or Dan Hill and (relatively) hoary veteran practitioners like Aron Pilhofer. Their experience has provided invaluable evidence for debugging debates about the topic.
That was certainly the case with Chase Davis, an assistant editor on the Interactive News Desk at the New York Times. I first me Chase in 2011 at the first Newsfoo, in Phoenix, Arizona, where he gave an Ignite talk on three news problems data science can help solve. Davis followed up in 2012 with an Ignite on using data to explore the evolution of data journalism. Both 5 minutes videos are well worth watching if you’re even remotely interested in journalism and technology. (Davis also open sourced his data journalism Ignite on Github, if you’d like to explore that way.)
Today, Davis teaches an advanced data journalism class at Mizzou, where he helps transfer his skills and perspective (treat data a source). Our interview, lightly edited for clarity, content and [bracketed] and hyperlinked for context, follows.
What is a day in your life like?
I help supervise the developer/journalists who build many of our cool Web projects. I have a background as a reporter, primarily doing investigations and covering politics, so I try to dabble in that world as well. I also teach a class in advanced data journalism at the Missouri School of Journalism and do some consulting on the side.
How did you get started? Did you get any special degrees or certificates? Quantitative skills?
I got started in data journalism almost by accident. I started learning to program for fun in middle school, then fell in love with journalism and ended up at Mizzou. I lived a typical j-student life for a few years, writing a bunch for the student paper and doing internships, then applied (based on a total misunderstanding) to start working for NICAR. The couple years I spent there really tied those two skillsets together.
Did you have any mentors? Who? What were the most important resources they shared with you?
Too many to list, but I’ll name a few. Jacquee Petchel, Lise Olsen and Mark Katches for schooling me in the ways of capital-J Journalism. Brant Houston and Jeff Porter for taking me in at NICAR and showing me how journalism and data can work together. And, really, the entire IRE and NICAR community, which is outrageously giving of its collective time.
What does your personal data journalism “stack” look like? What tools could you not live without?
I’m pretty minimalist: a terminal window and some type of text editor. The only place I splurge is on a database GUI (I like Navicat). The one tool I couldn’t live without is Python, which is the best Swiss Army knife a data journalist can have.
What are the foundational skills that someone needs to practice data journalism?
The same core skills you need to practice any kind of journalism: curiosity, skepticism, an eye for detail and a sense of a good story. [They] also [need] numeracy, or at least conceptual mathematical literacy, which is still unfortunately too rare. Also important are databases and spreadsheets, statistics, and some kind of programming language — doesn’t matter which one. Being your own worst critic doesn’t hurt. And intellectual courage. You need to be motivated, not intimidated, to learn new and difficult things.
Where do you turn to keep your skills updated or learn new things?
Personal projects. I always have at least one on the backburner, and I make sure it stretches me in a new direction. Working on something I care about is the best way for me to stay motivated. I get bored learning from books.
What are the biggest challenges that newsrooms face in meeting the demand for people with these skills and experience? Are schools training people properly?
The oversimplified explanation is that most journalism students can’t code or do math, while most computer science students don’t know storytelling.
Hybrids on either side are rare, and we’re scooping them up as fast as we can.
Folks on our interactive and graphics teams at the Times have remarkably diverse backgrounds: journalism and computer science, sure, but also cartography, art history, and no college degree at all. What makes them great is that they have an instinct to self-teach and explore.
That’s what journalism schools can encourage: introduce data journalism with the curriculum, then provide a venue for students to tinker and explore. Ideally, someone on faculty should know enough to guide them. The school should show an interest in data journalism work on par with more traditional storytelling.
Oh, and they should require more math classes.
What data journalism project are you the most proud of working on or creating?
Hard question, but I’ll offer up pretty much anything that my old team at the Center for Investigative Reporting has done. That was my first turn at being a boss, and the fact that they haven’t all been fired suggests that I didn’t mess them up too bad.
What data journalism project created by someone else do you most admire?
Look at the Philip Meyer Awards every year and you pretty much have that answer. Anyone who can take a spreadsheet full of rows and columns, or a bunch of code, and turn it into something that changes (or starts) the conversation about an important topic is the whole reason many of us got into this game in the first place.
How has the environment for doing this kind of work changed in the past five years?
It’s night and day. Five years ago, this kind of thing was still seen in a lot of places at best as a curiosity, and at worst as something threatening or frivolous. Some newsrooms got it, but most data journalists I knew still had to beg, borrow and steal for simple things like access to servers.
Solid programming practices were unheard of — version control? What’s that? If newsroom developers today saw Matt Waite’s code when he first launched PolitiFact, their faces would melt like “Raiders of the Lost Ark.”
Now, our team at the Times runs dozens of servers. Being able to code is table stakes. Reporters are talking about machine-frickin’-learning, and newsroom devs are inventing pieces of software that power huge chunks of the web. The game done changed.
What’s different about practicing data journalism today, versus 10 years ago?
It was actually 10 years ago that I first got into data journalism, which makes me feel old even though I’m not.
Back then, data journalism was mostly seen as doing analyses for stories. Great stories, for sure, but interactives and data visualizations were more rare.
Now, data journalism is much more of a Big Tent speciality. Data journalists report and write, craft interactives and visualizations, develop storytelling platforms, run predictive models, build open source software, and much, much more. The pace has really picked up, which is why self-teaching is so important.
Is data journalism the same thing as computer-assisted reporting or computational journalism? Why or why not?
I don’t think the semantics are important. Journalism is journalism. It should be defined on its own merits, not by the tools we use to accomplish it. Treating these things as exotic specialties makes it too easy to pigeonhole the people who practice them. And I hate that.
What’s the one thing people always get wrong when they talk about data journalism?
That data journalists are unicorns.
— Alex Howard (@digiphile) April 4, 2014
Or wizards. Or that they can somehow pull swords from stones in a way that mere laypeople can’t. That kind of attitude is dangerous — not because it mythologizes tech skills, or demonstrates willful ignorance on the part of technophobes (both of which are sad), but because it drives a cultural wedge between data journalists and the rest of the newsroom.
[Imagine hearing] “I’m a conventional reporter, so my specialty is reporting. You’re a tech person, so you write code.”
I think that’s crap. I know plenty of reporters who can code, and plenty of data journalists who can report the hell out of a good story. By dividing them culturally, we almost let people see the “journalist” in “data journalist” as secondary. We turn them into specialists, rather than letting them bring journalism and technology together in new and creative ways.
Why are data journalism and “news apps” important, in the context of the contemporary digital environment for information?
Numeracy is important. A more universal appreciation of technology in our industry is important. A culture of rapid, constant experimentation is important. To the extent that data journalism has encouraged those things in newsrooms, I think it’s been hugely important.
The actual product of data journalism — news apps, visualizations, stories — those will all continue to evolve, but data journalism’s continuing contribution to newsroom culture is something that I hope is permanent.