Seed Grants (max. $25,000)

We are accepting proposals for smaller grants that require support for a particular need, or for early-stage or exploratory projects. We welcome proposals to fund undergraduate or graduate involvement. Projects of this size may involve either single or multiple faculty, postdoctoral scholars, or staff.

Collaborative Grants ($25,000-60,000)

To increase significant data science research on Brown’s campus, DSI also seeks proposals for larger grants that involve collaboration among domain researchers and data science faculty. We will prioritize new initiatives and collaborations. Projects of this size will typically involve multiple faculty, postdoctoral scholars, or staff. We are particularly interested in projects that lead to additional external funding in data science or in data-intensive domain disciplines. DSI might, for example, may share the cost of a postdoc to bring new data science knowledge and skills that enable new research directions in a lab.

We fund proposals that are aligned with the mission of DSI (see above) and that 

• initiate a new interdisciplinary research direction or catalyze new collaborations across disciplines or units, potentially leading to a competitive external grant proposal; or
• advance Brown’s educational goals in data science. 

Successful proposals should address at least one of these criteria.

We fund proposals that are aligned with the mission of DSI (see above) and that

• initiate a new interdisciplinary research direction or catalyze new collaborations across disciplines or units, potentially leading to a competitive external grant proposal; or
• advance Brown’s educational goals in data science. 

Successful proposals should address at least one of these criteria.

Our annual Call for Proposals generally goes out in mid-March.

Proposals should be up to 5 pages long and address the following:

• Context and background (Why will people care?)
• Project summary (What will you do?)
• How does your proposal address our criteria and mission? What is new and why should we fund you? (Why is DSI the right funding source?)
• What are your measures of success? (What will be the outcomes?)
• Timeline and budget (including budget justification and other sources of current or pending funding) (What will it cost and how long will it take?)

Proposals should be written with a broad audience of scholars in mind. We encourage applicants to list at least two potential reviewers at Brown in their proposal. Proposals are submitted to dsi-info@brown.edu.

Proposals are generally due mid March.

Proposals will be reviewed by a DSI committee (and potentially other Brown ad hoc reviewers). We will evaluate proposals on the basis of the criteria mentioned above, the anticipated risks and rewards of the proposed project, and the proposed budget.

Successful applicants will be expected to

• provide a brief description of their project with an image for the DSI website;
• work with a DSI liaison to keep track of progress (for collaborative grants only);
• attend and present at a 2-hour annual gathering of grant recipients;
• provide a written 1-2 page final report of findings and outcomes.

Award recipients are notified at the end of the spring semester with awards granted for use during the upcoming fiscal year (July - June.)

Please submit proposals to dsi-info@brown.edu with the subject line “DSI Seed and Pivot Grants”.

Projects that we would be interested in funding include, but are certainly not limited to:

• Working lunches/discussion groups to bring together colleagues from different units or disciplines to work on a competitive grant proposal or develop new research directions;
• Preliminary data collection and analysis for preparing an external funding proposal;
• Purchase of data from social media platforms or subscription-based data providers, for instance to facilitate a student research project or course;
• Graduate student or postdoc funding, for initiating a new interdisciplinary data science research project;
• Course development of co-taught courses at the interface between data science and other disciplines;
• Data science workshops for undergraduate or graduate students intended for audiences from multiple disciplines;
• Bringing in high-profile visitors for lectures or collaborations;
• Workshop development to improve the data literacy of the general Brown community (faculty, students, staff).