Features / How-to
Good docs help people use your work, but they have other benefits too. They encourage community contributions. They save you from your past self when you’re revisiting your own code six months from now. And they help you think: much like talking to a rubber duck helps you find bugs, carefully documenting your work for users helps you see it from a different perspective and design better code.
“Someone could screw it up” is a terrible excuse not to cede control. We hear it often as a defense of why a newsroom doesn’t let its reporters make their own charts. It sounds reasonable enough, but when you consider the deluge of other types of content that come out of a newsroom getting swiftly edited to the highest standard, it becomes easy to see how the possibility of “screwing it up” is a terrible excuse. It’s time to think about and produce graphics in the same way that we do paragraphs: crafted by a reporter and vetted by an editor for both substance and style.
Last Friday morning, Jessica Garrison, Ken Bensinger, and I published a BuzzFeed News investigation highlighting the ease with which American employers have exploited and abused a particular type of foreign worker—those on seasonal H–2 visas. That same morning, we published the corresponding data, methodologies, and analytic code on GitHub. This isn’t the first time we’ve open-sourced our data and analysis; far from it. But the H–2 project represents our most ambitious effort yet. In this post, I’ll describe our current thinking on “reproducible data analyses,” and how the H–2 project reflects those thoughts.
This week, the Texas Tribune launched Faces of Death Row, a simply designed news app that prominently features photographs of each of the 261 people currently awaiting execution in Texas (accompanying article). The app allows for filtering by age, race, sex, and number of years spent on death row. Its simplicity—an artifact of the unavailability of the data the Tribune originally sought—is also its strength.
How ProPublica’s team communicated the complexities—and absurdities—of $2B in mostly unrestricted spending by military personnel in Afghanistan.
When and how to say goodbye to the bots when something has gone terribly wrong…or when no one’s really laughing anymore.
A Node-based Twitter bot, one easy step at a time—plus the way John Keefe teaches basic botmaking to class of journalism/design students.
Twitter’s data editor lays out the major challenges and opportunities that arise when you set out to map tweets.
An exploration of an easy way to animate paths in SVG maps.
Job hunting can be an intimidating process, especially for recent grads or people looking to break into a new field. The journalism tech community is a welcoming place for new faces and Sisi Wei and Jeremy B. Merrill want to help you overcome any fears and apply for jobs and internships in this growing and evolving field.
Not sure where to begin with this whole bot thing? Joseph Kokenge is here to help you get started with botmaking 101.
Alyson Hurt digs into the challenges of producing legible, useful network diagrams using evolving web technologies and methods.
Jacob Harris on the challenges of reporting and calling elections and the making of the NYT’s chart of minute-by-minute Virginia governor’s race reporting action.