From ProPublica by Rachel Glickhouse
We’ll be expanding and open-sourcing the tools we created to do Documenting Hate, as well as Electionland, and writing a guide that will let any newsroom do crowd-powered data investigations.
Today we’re announcing new tools, documentation and training to help news organizations collaborate on data journalism projects.
Newsrooms, long known for being cutthroat competitors, have been increasingly open to the idea of working with one another, especially on complex investigative stories. But even as interest in collaboration grows, many journalists don’t know where to begin or how to run a sane, productive partnership. And there aren’t many good tools available to help them work together. That’s where our project comes in.
We’ll be sharing some of the software we built, and the lessons we learned, while creating our Documenting Hate project, which tracks hate crimes and bias-motivated harassment in the U.S.
The idea to launch Documenting Hate came shortly after Election Day 2016, in response to a widely reported uptick in hate incidents. Because data collection on hate crimes and incidents is so inadequate, we decided to ask people across the country to tell us their stories about experiencing or witnessing them. Thousands of people responded. To cover as many of their stories as we could, we organized a collaborative effort with local and national newsrooms, which eventually included more than 160 of them.
We’ll be building out and open-sourcing the tools we created to do Documenting Hate, as well as our Electionland project, and writing a detailed how-to guide that will let any newsroom do crowd-powered data investigations on any topic.
Even newsrooms without dedicated developers will be able to launch a basic shared investigation, including gathering tips from the public through a web-based form and funneling those tips into a central database that journalists can use to find stories and sources. Newsrooms with developers will be able to extend the tools to enable collaboration around any data sets.
Full article at ProPublica