Tasneem Raja urges newsrooms to adopt pair programming for better data journalism
New, digitally native media enterprises like Five Thirty Eight have gotten a lot of attention — and some grief — as they’ve gone online this year. It’s media organizations and journalists at them that were born in print, however, that pioneered the practices of computer-assisted reporting that underpin the news apps and data journalism of today. The New York Times’ Upshot is just the latest addition to these efforts.
Tasneem Raja, the interactive editor at Mother Jones Magazine, knows this reality well. She’s one of the growing number of journalists who aren’t just reporting upon the news but building the medium for the message to be communicated. Before she joined Mother Jones, was the news apps editor at The Bay Citizen, where her team built a Bike Accident Tracker and a government salary database, among other things, and a feature writer at The Chicago Reader. Raja’s insights into how to build an interactive news team (more on that below) are well worth reading. You can follow her work on Github or her commentary on Twitter. Our interview follows, lightly edited and linked for context.
Where do you work now? What is a day in your life like?
I’m a senior editor at Mother Jones magazine, where I lead an awesome team of data reporters and interactive producers. I’m also a writer and reporter, in print and on the Web.
We live by a few guiding principles on my team. The big one is that it’s our job to make sure everybody in the newsroom can tell a story by any means necessary. That is, reporters should know how to map, the mapmaking pros on my team should know how to factcheck, the fact checkers should know when to use a column chart versus a bar chart, and so on. We don’t believe in siloed skills.
Of course, some folks will always be way better at some skills than others, but you gotta pay it forward, which brings me to our second guiding principle: we are all learners, and we are all teachers.
Put it all together, and you get quite the three-ring circus of hybrid journalism going on here everyday. Today, for instance, I’m finishing up edits on a big magazine feature story about the future of programming, while teaching Illustrator charting to a reporter with good data on air pollution. Producer Jaeah Lee is teaching a reporter best practices in structured data for an easy-to-update map of gay marriage laws. Our interactive fellow AJ Vicens just fired off a quick blog post about racism in sports, and is now working with a reporter on abstracting an open-source template we made. We probably look pretty different than most data teams in this way.
How did you get started in data journalism? Did you get any special degrees or certificates?
I was a staff writer at the Chicago Reader in the mid-2000s, which was, of course, a scary time to be in news. When a bunch of my senior mentors there, all writers, got canned in 2007, I decided to re-evaluate my career and went to j-school at Berkeley to learn new skills. I was lucky enough to be there while Josh Williams was teaching web development (he left for the NYT, where he worked on Snowfall and tons of other big interactive pieces), and essentially attached myself at the hip. It turned into a year-long independent study, and got me a job on the launch team at The Bay Citizen, where I created a news apps team that made some really cool data projects for the Bay Area (RIP, TBC).
What quantitative skills did you start with?
I’ve always appreciated structured ways of looking at information. There’s something about well-formatted tables of information and clean spreadsheets that makes me really happy. That’s the most important skill for a data journalism, in my opinion: a love of working with structured data, and creating whole new systems and worlds atop it. That strange love is what makes you want to put the time in to learn R, command line tools, pivot tables, and so on – all stuff I didn’t pick up ’til halfway through my first job in data journalism.
Did you have any mentors? Who? What were the most important resources they shared with you?
“Mentor” is a funny word. Here are a few people who’ve left deep thumbprints on the way I think about my work (whether they intended to or not).
Josh Williams taught me everything I needed to know to get a really good first job in data journalism and news apps: what’s a text editor, what’s the command line, what’s a Web framework. More than that, he got me thinking in terms of abstraction. For instance, he was always saying, “Never build something you can only use once.” Instead, think both in terms of the specific needs of the project in front of you, and the broader needs of a similar project you might not even know of till next year. Seeing the way he held both of these concepts in his head at once was an incredible lesson in how to be a journalist who is also a pretty decent project manager.
Brian Boyer taught me the importance of having a guiding philosophy (or three) to your work. The why of what you do, not just the how. And that your philosophies can sound more like something a chef or a potter would say, than a data nerd. In other words, he got me thinking about this work as craft.
Scott Klein has inspired me to better know my shit. That is, it’s not enough to read a few blog posts about data journalism and crown yourself the next Edward Tufte. There’s a lot of history to what we do, a lot of important choices to be made, and fortunately, there are very old and very new books out there to learn from. You can’t have a conversation with Scott without wanting to go pick up a book.
What does your personal data journalism “stack” look like? What tools could you not live without?
1. A good, simple text editor, with good syntax highlighting
2. A spreadsheet app, with version control and collaborative editing
5. The cognitive ability to think in terms of abstraction
Where should people who want to learn start?
A hundred people have said it before me, and better: pick a project you genuinely want to do, and then hack, Google, and plead for help in forums, and read books, until you get it working.
Where do you turn to keep your skills updated or learn new things?
1. The NICAR conference
3. Increasingly, printed books
4. Dissecting the work of colleagues at other shops
What are the biggest challenges that newsrooms face in meeting the demand for people with these skills and experience? Are schools training people properly?
There are a ton of challenges, so I’ll pick one: we don’t have a pair programming model on the editorial side of the newsroom, and we need one.
Journalism schools still teach journalism as a very hierarchical, often solitary pursuit. That’s not the way it works in data journalism, and the best learning is still gonna be on the job. That requires cross-pollination between folks with different skill sets. We need a pairing model across newsrooms, not just in the nerd corner.
I’ve had several people tell me they’re surprised to learn how small my team is, given the daily volume of content we put out. That’s because we’re not the only ones who can work with data and visuals in our newsroom. W’ve spent serious time pairing with something like 1 in 3 staffers here, working and training side by side whenever physically possible. (We have offices on different coasts). We’ve gotten several editors and reporters on Github, and while we don’t have them checking in code through the command line (yet), they’re well-versed in the how and why of version control.
What’s the one thing people always get wrong when they talk about data journalism?
That it’s all quantitative. That’s like guiding principle #3 on my team: everything is data. Words are data. Gifs are data. If it can be sorted, tracked, counted, merged, filtered: it’s probably data. I’d say half the project my team does is more qualitative than quantitative. That is, most people wouldn’t consider it data visualization so much as photo essays, games, quizzes, etc. There’s a lot of power in developing a data skill set — both technical and cognitive — that lets you make cool things with words and pictures, too.
You’re written about Silicon Valley’s “brogrammer problem.” How do data journalists and their communities of practice handle issues of race, sexism or gender?
NICAR is a pretty healthy place to be a non-white, non-male person working in journalism. I can’t speak to issues of class, ability, gender identity, and other types of difference, other than to say we’re almost definitely less good at them, and that needs to change.
I don’t have experience with the way folks in this community handle issues of inclusion issues when they come up, but I have seen evidence of folks working to preemptively to create environments that are more less exclusionary than the norm in web development, quantitative analysis, the visual arts, or journalism. Maybe it’s because there haven’t been that many of us webby data journos till recently. Data journalists are pragmatic by nature, and maybe it just didn’t make sense to alienate potential swaths of new recruits.
That’s not to say everything is rainbows and sunshine, but I’m gonna take a rare moment of optimism here and say that I’m proud to represent this community, because in my experience, it’s genuinely committed to inclusion.