Taking a break from Twitter • Human @ Internet • Data Editor @ BuzzFeed News • Newsletter-er @ https://t.co/t7klYZ4pkb
Jeremy’s work on Source
- An Open Guide to Zika Data
- What We’ve Learned About Sharing Our Data Analysis
- When the News Calls for Raw Data
- All About Reporter
Articles by Jeremy
An Open Guide to Zika Data
Finding and curating datasets for an open guide, when data is scarcePosted on
Over a month after Brazil declared a state of emergency in response to a Zika outbreak, clear information on the virus is hard to come by. On Monday, BuzzFeed’s Jeremy Singer-Vine started an open guide to Zika-related data, to collect what we do know and help other journalists do the same. It points to resources like global and country-specific data on the spread of the virus, its mosquitos, and microcephaly, from respected sources. We asked why he started it, how he curates it, and where he can use everyone’s help.
What We’ve Learned About Sharing Our Data Analysis
Publishing reproducible data that’s genuinely usefulPosted on
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.
When the News Calls for Raw Data
Thoughts on recent dataset postings from BuzzFeed and the New York TimesPosted on
We spoke with the NYT and BuzzFeed about recent data postings prompted by the news from Ferguson, MO.
All About Reporter
News developer Jeremy Singer-Vine introduces a tool for a divided readershipPosted on
The Wall Street Journal’s Jeremy Singer-Vine recently released Reporter, an open source tool that makes it easy to hide and reveal the code behind common forms of data visualization presented on the web. We spoke with him about the tool’s makeup, design goals, and future development plan.