“I want to be a data journalist.”
It’s been over a year since these words went through my head. At the time, I was an economic research analyst in D.C. with literally zero news experience. A lot has happened since then, and I’m now three months into a ten-month Knight-Mozilla Fellowship at the L.A. Times Data Desk.
I’ve always believed that you can’t know what a job is really like until you’re doing it yourself. In my short time as a Fellow, I’ve already learned so much.
Some of what I’ve learned probably falls under “Stuff from Journalism School”; e.g., what “slot” and “slug” mean, how to interview people, who Strunk and White are; or “Stuff from the world of Computer Science / Software Development / Coding”; e.g., what Django is & why it’s so powerful, how Jupyter notebooks can be the future of code-sharing, the pros and cons of Python and R, etc.
Some of it deals with broader questions:
- What makes something “journalistic”?
- What makes something “newsworthy” (and is this the same thing as “journalistic”)?
- What is “data” journalism, and (why) does it have to be separated from “traditional” journalism?
- What about “empirical” journalism?
- Is (data) journalism becoming more like social science, and vice versa?
- If so, as journalists, how can we “peer review” our data stories?
- What is journalistic instinct, and do I have it?
I’m writing this blog as a way to chronicle my learning, as I sort through these questions and more. I hope it’s as helpful to you as it is to me.
And for the record, I’m thrilled that these days, I get to say the words out loud:
“I’m a journalist.”