Projects submitted to the Data Journalism Awards competition

Right here you will find a list of all the projects submitted to the Data Journalism Awards competition.  

Graphics at The New York Times Opinion
Country: United States
Organisation: The New York Times
Best data journalism team
Sensor
Immersive
Interactive
Investigation
Collaboration
Maps
Visualisation
Verification
Election
Sports
Health & Science
Environment
Economy
Applicant
Stuart
Thompson
Team Members
Jessia Ma Bill Marsh
Project Description
Data can be an incredible tool for changing minds. At the newly expanded graphics department at the New York Times Opinion section, we have tried using data in the service of opinionizing. In our first year, this somewhat novel experiment produced a breadth of work, from cataloguing Trump’s lies to exposing the conditions that enabled the flooding in Houston.
What makes this project innovative?
The breadth of work here includes traditional data journalism alongside interactives, animation, timelapse maps, illustration and design to create compelling and convincing arguments from a specific point of view. Our gun calendar piece, in particular, was noteworthy because it visualized the absence of data – a perspective might seem more appropriate in Opinion rather than the newsroom.
What was the impact of your project? How did you measure it?
“Trump’s Lies” went viral and was covered on national television networks and across the internet, becoming a touchstone on social media and in the national conversation about Trump’s honestly. Our work on gun violence exposed the inexcusable lack of action from Congress on implementing any meaningful form of gun control. Soon after our series on the connection between domestic violence and gun control was published, the N.R.A. came out in support of additional legal measures to prevent abusers from owning guns.
Source and methodology
We used a variety of sources and collaborated with researchers, think tanks and other organizations to complete our analysis in these projects.
Technologies Used
Most of the visualizations here used D3.js or other Javascript libraries. Data was often processed in Node, R or Excel. Illustrator was used for static charts.