“Stories can be told in many different ways,” said Cheryl Phillips. “A sidebar that may once have been a 12-inch text piece is now a timeline, or a map.”
Phillips, an award-winning investigative journalist, will begin teaching students how to treat data as a source this fall, when she begins a new gig as a lecturer at Stanford’s graduate school of journalism helping to open up Stanford’s new Computational Journalism Lab.
“Cheryl Phillips brings an outstanding mix of experience in data journalism and investigative work to our program. Students and faculty here are eager to start working with her to push forward the evolving field of computational journalism,” said Jay Hamilton, Hearst Professor of Communication and Director of the Stanford Journalism Program, in a statement. “Her emphasis on accountability reporting and interest in using data to lower the costs of discovering stories will help our journalism students learn how to uncover stories that currently go untold in public affairs reporting.”
I interviewed Phillips about her career, which has included important reporting on the nonprofit and philanthropy world, her plans for teaching at Stanford, data journalism, j-schools and teaching digital skills, and the challenges that newsrooms face today and in the future.
What is a day in your life like now?
I’m the data innovation editor at The Seattle Times. Essentially, I work with data for stories and help coordinate data-related efforts, such as working with reporters, graphics folks, and others on news apps and visualizations. I also have looked at some of our systems and processes and suggested new, more time-effective methods for us.
I’ve been at The Seattle Times since 2002. I started as a data-focused reporter on the investigations team, then became deputy investigations editor, then data enterprise editor. I also worked on the metro desk and edited a team of reporters. I currently work in the digital/online department, but really work across all the departments. I also helped train the newsroom when we moved to a new content management system about a year or so ago. I am trying to wrap up a couple of story-related projects, and do some data journalism newsroom training before I start at Stanford in the fall.
How did you get started in data journalism? Did you earn any special degrees or certificates?
I remember taking a class (outside of the journalism department) while in college. The subject purported to be about learning how personal computers worked but, aside from a textbook that showed photos of a personal computer, we really just learned how to write if, then loops on a mainframe.
I got my first taste of data journalism at the Fort Worth Star-Telegram. That’s where I did my first story using any kind of computer for something other than putting words on a screen. I had gotten the ownership agreement for the Texas Rangers, which included a somewhat complex formula. I kept doing the math on my calculator and screwed it up each time. Finally, I called up a friend of mine who was a CPA, and she taught me Lotus 1-2-3.
My real start in computer-assisted reporting came in 1995, when I was on loan to USA TODAY. I was fortunate enough to land in the enterprise department with the data editors, and Phil Meyer was there a consultant. By the end of five months, I could use spreadsheets, Paradox (for DOS!) and SPSS. What a great education. I followed that up by joining IRE and attending the NICAR conference. I’ve missed very few since then and also done some of NICAR’s specialized training on stats and maps.
I have no special degrees or certificates, but I have taken some online courses in R, Python, etc.
Did you have any mentors? Who? What were the most important resources they shared with you?
Phil Meyer is amazing, and such a great teacher. He taught me statistics, but also taught me about how to think about data. Sara Cohen and Aron Pilhofer of the New York Times, and Jennifer LaFleur of CIR. Paul Overberg at USA TODAY. They have all helped me over the years.
NICAR is an incredible world, full of data journalists and journalist-programmers who are willing to help others out. It’s a great family.
On the investigative journalism front, Jim Neff and David Boardman are fantastic editors and great at asking vital questions.
What does your personal data journalism “stack” look like? What tools could you not live without?
I’m a firm believer in the power of the spreadsheet. So much of what journalists do on a daily basis can be made easier and more effective by just using a spreadsheet.
I use OpenRefine, CometDocs, Tabula, AP Overview and Document Cloud. I use MySQL with Navicat. I still use Access. I’m a recent convert to R, but also use SPSS. I use ESRI for mapping, but am interested in exploring other options also. I use Google Fusion Tables as well.
Most of my work has been in more of the traditional CAR front, but I’ve been learning Python for scraping projects.
What are the foundational skills that someone needs to practice data journalism?
In many ways, the same foundational skills you need for any kind of journalism.
Curiosity, for one. Journalists need to think about stories from a mindset that includes data from the very beginning, such as when a reporter talks to a source, or a government official. If an official mentions statistics, don’t just ask for a summary report, but ask for the underlying data — and for that same data over time. The editors of those reporters need to do the same thing. Think about the possibilities if you had more information and could analyze and view it in different ways.
Second, be open to learning any skill sets that will help tell the story. I got into data journalism because I discovered stories I would not be able to tell if I didn’t obtain and analyze data. We all know journalists don’t like to take someone’s word for something — data journalism just takes that to the next level.
Third, in terms of technical skills, learn how to use a spreadsheet, at a bare minimum. Really, one tool leads to another. Once you know how a spreadsheet works, you are more open to using OpenRefine to clean and standardize that data, or learning a language for scraping data, or another program that will help with finding connections.
What classes will you be teaching at Stanford, and how?
I will be teaching several courses, including a data journalism class focusing on relational data, basic statistics and mapping. I also will be teaching an investigative reporting class focusing on investigative reporting tools.
In general, I want to make sure the students are telling stories from data that they analyze. They should be not only learning the technical stack, but how to apply the technical knowledge to real-world journalism. I am hoping to create some partnerships with newsrooms as well.
Where do you turn to keep your skills updated or learn new things?
IRE and NICAR and all the folks involved there. I also try to learn from our producers at The Seattle Times, who come in knowing way more than I did when I started in journalism. I try to follow smart people on Twitter and other social media.
I like to reach out to folks about what they are doing. I think reaching out and connecting with folks outside of journalism is a great way to make sure we are aware of other new tools, developments, etc.
What are the biggest challenges that newsrooms face in meeting the demand for people with these skills and experience?
Newsrooms are often still structured into silos, so reporters just report and write. They may hand their data off to a graphics desk, but they don’t necessarily analyze or visualize data themselves. Producers produce, but don’t write, even though they may enjoy that and be good at it, too.
Some of this is by necessity, but it makes it harder to learn new skills — and some of these skills are really useful. A reporter who knows how to visualize data may also be able to look at in a different way for reporting the story out too. So, building collaborative teams is important, as is providing time for folks to try out other skills.
Are journalism schools training people properly? What will you do differently?
I think it’s no secret that a lot of change is starting to take place in schools.
Cindy Royal had an interesting piece aboutplatforms just the other day. In general, I think my answer here is similar to the biggest challenge for newsrooms: We need to take a more integrated approach. Classrooms and their teachers should collaborate on work.
So, for example, a multimedia class produces the visualizations and videos that go with the stories being written in another class. (Yes, Stanford already does this.)
Data journalism should not be just one class out of a curriculum, but infused throughout a curriculum. Every type of journalist can learn data-related skills that will help them, whether they end up as a copy editor, a reporter, a front-line editor or a graphics artist.
What data journalism project are you the most proud of working on or creating?
I have been asked this question before and can never answer it well. My last story is always the one I’m most proud of, unless it’s the one I’m about to publish.
That said, as an editor at The Seattle Times, I worked with Jennifer LaFleur (then with ProPublica) on a project tracking the reasons behind foreclosures, a deep dive into the driving factors behind foreclosures from several cities.
When I was a reporter, I was lucky enough to get to work with Ken Armstrong on our court secrecy project in 2006, which changed state practice. I also led the reporting effort on problems with airport security. Both of those used small data sets, which we built ourselves, but told important stories.
I can think of even more stories that weren’t data projects per se, but which used data in the reporting in critical ways. The recent Oso mudslide coverage is an example of where we used mapping data and landslide data to effectively tell the story of the impact of the slide on the victims and of how the potential disastrous consequences had been ignored over time.
What data journalism project created by someone else do you most admire?
Too many to count. There has been so much great work done. ProPublica’s Dollars for Docs was fantastic not only for its stories, but the way they shared the data and the way newsrooms from across the country could tap into the work. Last year, the Milwaukee Journal Sentinel’s project,Deadly Delays, was such important work.
How has the environment for doing this kind of work changed in the past five years?
It’s much more integrated into new immersive storytelling platforms. There is a recognition that stories can be told in many different ways. A sidebar that may once have been a 12-inch text piece is now a timeline, or a map.
I think there are many more team collaborations, with the developers, designers and reporters and CAR specialists working together from the outset. We need a lot more of this.
What’s different about practicing data journalism today, versus 10 years ago? What about teaching it?
There are more tools, with more coming every day. A few are great, and a lot aspire to be great and some of those will probably get there.
The really fantastic thing about the change is that it’s relatively easy to contribute to the development of a tool that will help journalism, even just as a beta tester.
There are more tech folk interested in helping make journalism better. We’re becoming a less insular world, and that’s a good thing.
Why are data journalism and “news apps” important, in the context of the contemporary digital environment for information?
News apps help tell important stories. It’s the same reason narrative is important.
It always should boil down to that: “does this tool, language, or app help tell a story?” If the answer is “yes,” and you think the story could be worth the effort, then the tool is important too.
What’s the one thing people always get wrong when they talk about data journalism?
I think I’ll have to punt on this one. As you have pointed out, data journalism is a big umbrella term for many different things — precision journalism, computer-assisted reporting, computational journalism, news apps, etc. — so it’s easy to have a different idea as to what it means.
[IMAGE CREDIT: University of Washington]