Seven fellows at the Donald W. Reynolds Journalism Institute who have been working on innovative projects that can benefit the journalism industry, over the past eight months, are wrapping up their projects. Six shared findings and insights from their projects, as well as links to resources during a recent Q&A webinar with the public. We’ve … Continued
Introducing DUG, our beta data unit guide Forget the gist of the photo up there—the one reading “data has a better idea.” I don’t buy it. (Lovely photo though, no?) Data rarely has a better idea, because data doesn’t think. People think. Sometimes data can help people think a little better. The problem is that … Continued
A brief intro to exploratory analysis In a recent paper, a pair of statisticians took a stab at outlining “the most important statistical ideas of the past 50 years.” Among them: “counterfactual causal inference, bootstrapping and simulation-based inference, overparameterized models and regularization, multilevel models, generic computation algorithms, adaptive decision analysis, robust inference, and exploratory data … Continued
As far as I can tell, the Internet is mostly duct-taped together. And why should visual journalism be any different? In a world of flashy D3.js wrappers and React components and the like, sometimes you just need a chart—and you need it as quickly as possible. In other words, you don’t need interactivity; you need … Continued
Over the course of this RJI fellowship, I’m working with the nonprofit environmental magazine Grist to think through what it’d mean to build out a national environmental data-journalism unit—and, in turn, to take what we learn at Grist and translate these lessons into guides for other small or nonprofit newsrooms that might find themselves interested in similar work.