The Pulitzer Center encourages proposals that use advanced data mining techniques, such as machine learning and natural language processing, to solve a data or reporting problem related to a journalistic investigation.
Recent grantees have used machine learning to reveal the true scope of oil-well abandonment in Texas; hold land banks accountable in Ohio; and map the proliferation of gold mines in the Amazon rainforest.
These projects harnessed machine learning to augment the reporters’ capacity to tackle big data and systemic issues. The reporters combined the use of machine learning with geospatial analysis, satellite imagery, and traditional shoe-leather reporting, among other approaches.
Another interesting characteristic of the projects we have supported so far is that they all involved collaborative work, whether across newsrooms or disciplines. We encourage journalists to seek smart partnerships that can complement their skills and perspectives.
We're seeking compelling data-driven storytelling—based on original and transparent data collection and analysis—that has the potential to shape public discourse and hold the powerful accountable.
For inspiration, check out the projects we have supported so far:
- “Waves of Abandonment” by Grist/Texas Observer (2021 University of Florida Award for Investigative Data Journalism, Small/Medium Newsroom). Here’s how the reporters leveraged machine learning to tell the story.
- Properties on the Precipice by Eye on Ohio. Also, read the project’s methodology explainer.
- “The Illegal Runways that are Swarming the Venezuelan Jungle,” by ArmandoInfo/El País
- “Falling Through the Cracks: Pandemic Exacts Heavy Financial Toll on Georgians,” by the Atlanta Journal-Constitution. Here’s a detailed explanation of the data methodology.
In this grant we encourage radical transparency and sharing of methodologies and code, including ethics considerations that informed the research and reporting as well as data limitations, so each story produced can serve as a blueprint for other newsrooms pursuing similar projects.
Frequently Asked Questions
Who is eligible to apply?
This opportunity is open to U.S. residents and journalists around the world. We are open to proposals from freelance data journalists, staff journalists, or groups of newsrooms working in collaboration on a data project idea. We want to make sure that people from many backgrounds and perspectives are empowered to produce data journalism. We strongly encourage proposals from journalists and newsrooms who represent a broad array of social, racial, ethnic, underrepresented groups, and economic backgrounds.
When will you be notifying applicants on whether they've been selected?
We review applications on a rolling basis, as soon as they are received, and typically notify applicants within a month if they're being considered for support. If there is some urgency to the field reporting, the applicant should state the reason in the application.
What is the budget range for the data journalism proposals?
We do not have a budget range for these Machine Learning Grants. We will consider projects of any scope and size and we are open to supporting multiple projects each year. Most awards for our past data journalism project support has been between $10,000-$25,000, but may be more or less depending on circumstances.
Do you pay stipends or salaries for freelance journalists?
We expect news organizations to pay journalists for their work, though in some cases, we may consider stipends to cover a reporter's time, if provided in the budget with an explanation. It is OK to include costs of contractors, such as data researchers or data visualization/story designers in your proposal and budget. Please do not include stipends for journalists/team members who are in the employ of newsrooms or are being paid by a publisher.