Seed Grants

The Data Science Initiative (DSI) is pleased to announce a rapid response seed grant opportunity to foster innovative research and collaboration in data science and artificial intelligence (AI). With a maximum of $15,000 available per project, this initiative aims to catalyze projects that address emerging research needs, including projects that involve outreach and engagement, in data science and AI. Priority will be given to those proposals that align with specific external funding opportunities. Applications will be reviewed and award notifications will be made within 3 weeks of submission.

Requirements:

Submit a 2-page final report detailing the outcomes of the project including details on how the budget was used, what the research outcomes were (e.g., a proposal for internal or external funding, a pilot study, data analysis, etc. ), and how the results will be leveraged for future funding. Grantees will be expected to notify the DSI when a proposal is submitted and the outcome of the proposal (won/lost) when it is known. Finally, the PI agrees to provide the DSI with an abstract and optional image which will be used for promotional purposes including in the annual Seed Grant Showcase (annually in December).

Eligibility Criteria:

1. Interdisciplinary Approach: Proposals should involve interdisciplinary collaboration, at least cross-departmental, however, cross-collegiate levels are preferred and demonstrate a clear integration of data science and AI methodologies.

2. Faculty and Researcher Teams: The principal investigator (PI) must be a faculty or research staff (P&A) with their primary appointment at the University of Minnesota. Collaborators from diverse backgrounds and disciplines are strongly encouraged. Adjunct or affiliated faculty are not eligible for funding under this program.

3. Two-Page Application: Applications must be concise, with no more than two pages of content (single-spaced, 12-point font), excluding references.

Proposal Requirements:

1. Research Need: Proposals must articulate a clear and compelling case for how the project addresses an emerging research need in data science or AI. There must be a specific funding opportunity identified for which the result of the rapid response work is needed. The proposal must demonstrate relevance to the funding opportunity and potential for external funding. Projects should outline innovative approaches or methodologies that push the boundaries of current data science and AI research.

Proposal Components: Applications should include the following components:

• Title of the Project
• Principal Investigator(s) and Collaborator(s) Information
• Project Summary (maximum 250 words)
• Relevance to one of the five MnDrive areas:  Robotics, Global Food, Environment, Brain Conditions, and Cancer Clinical Trials, if applicable
• Research Plan, including:
  • Background and Significance
  • Project Objectives 
  • Methods and Approach
  • Expected Outcomes and Impact
• References (not included in page count)
• A 1-page budget justification with 
  • A clear budget breakdown outlining anticipated expenses noting any current and pending support, and/or existing funding to support for the proposed work

Review Process:

1. Peer Review: Proposals will undergo a rigorous peer review process by experts in the relevant fields.

2. Criteria: Evaluation will be based on the clarity and significance of the research need, innovation of the proposed approach, feasibility of the project, and potential for external funding.

Notification: Applicants will be notified of the decision by a later date.

DSI Faculty Fellowships are intended to promote, catalyze, accelerate, and advance UMN-based collaborations in data science and AI research so that UMN faculty and staff are better prepared to compete for external funding opportunities. Faculty with research in data science and AI in all disciplines and across all campuses, including interdisciplinary collaborations intersecting with Data Science and AI are encouraged to apply for this fellowship.

The DSI faculty fellow will pursue 1-2 specific grant opportunities as a result of their participation in the program. The DSI faculty fellows are expected to nurture and lead interdisciplinary teams to pursue large-scale proposals where DS/AI is central to their success. Of special interest are projects that may require long-term planning and leverage unique UMN strengths (as reflected in faculty expertise, facilities, or data sets) and priorities. This initiative seeks to lower barriers to multidisciplinary collaborations and to accelerate the advancement of data science and AI research by providing faculty with financial support (see below) and grant organization and writing assistance.  Assistance will be tailored to help identify funding opportunities that require or prioritize interdisciplinary collaborations. The DSI is prepared to assist in facilitating these multidisciplinary collaborations at all levels including organizing meetings and facilitating introductions to other experts needed to strengthen a team,  as well as pre- and post- grant administration and technical writing. At least one funding opportunity must be identified in the proposal.

Requirements:

The faculty fellow will have regular check-ins with DSI leadership to ensure they are receiving the needed support. A no more than 5 page final report will be delivered to the DSI upon completion of the fellowship term detailing the outcomes of the fellowship, the funding proposals submitted and their current status, future plans, and the budget details.  Grantees will be expected to notify the DSI when a proposal is submitted and the outcome of the proposal (won/lost) when it is known. Five percent of the ICR for all award applications submitted during the fellowship period will be retained by DSI to support core activities.  The DSI will work with the appropriate leadership in the applicants' department and/or college for any paperwork required. Finally, the faculty fellow agrees to provide the DSI with an abstract and optional image which will be used for promotional purposes including in the annual Seed Grant, Faculty Fellowships, and Data Sets Showcase (annually in December).

Funding Details:

• DSI Faculty Fellows will receive up to $75,000 towards a course buyout, graduate research assistant support, or travel support to related conferences or professional meetings, career development, and so on. Contact [email protected] with questions concerning qualified fellowship expenses.
• Professional organizational and grant-writing assistance will be provided
• Workspace will be provided at the DSI office (Johnston Building, 4th floor)
• Recognition on the DSI website, including name and headshot.

Eligibility: Regular (Tenured and Tenure-Track) Faculty with their primary appointment at the University of Minnesota with a research area related to, encompassing, or using data science or AI throughout the UMN system are eligible to apply to be a faculty fellow. Adjunct, Affiliated, or Term Faculty are not eligible for funding under this program.

Application Requirements:

Interested faculty members are invited to submit a proposal of no more than 5 pages, addressing the following:

Introduction:

• A brief overview of the research which will be the basis for the terms proposal(s)  
• Identification of targeted funding opportunities, identification of team (specific persons or expertise needed).
• Relevance to one of the five MnDrive areas:  Robotics, Global Food, Environment, Brain Conditions, and Cancer Clinical Trials, if applicable

Interdisciplinary Nature:

• Explanation of how the proposed project bridges multiple disciplines.

Anticipated Impact:

• Discussion of the potential impact of the research on data science and related disciplines. Background on the current research in this area at the UMN and elsewhere.

Budget and Timeline:

• Itemized budget detailing how the funds will be utilized.
• Proposed timeline and milestones for project execution.

Applicant Information:

• Brief biography highlighting relevant expertise and experience.
• Statement of commitment to collaboration and engagement with the DSI.

The DSI is committed to fostering innovative research and collaboration in data science. We look forward to supporting faculty members in pursuit of impactful interdisciplinary projects.

Up to $100,000 for 1-2 years, quarterly deadlines.

Up to $200,000 for a data set or $100,000 for prelim data set with the intent to submit a proposal for infrastructure

This program aims to foster research that creates or expands novel data sets, which are crucial for advancing innovative research in diverse fields. This initiative seeks to address the critical need for high-quality data by providing funding and support for projects that generate, enhance, and annotate data sets to fuel cutting-edge research at the University of Minnesota (UMN). Successful applications will demonstrate how these data sets are valuable beyond any single lab. The value may come from industry partners (particularly those based in MN or those with a strategic value in MN) or other research entities. 

Requirements:

The PI will deliver a 2-page progress report to the DSI detailing the current status of the timeline, milestones, and budget information. Upon completion of the project, the data set must be uploaded to a UMN-owned data repository. A manual for usage including an overview of the data set, types of research the data could be used for, detailed meta-data, and methods of data collection must be uploaded with the data set. Evidence that the data set has value to groups other than those generating it.  Value can be measured in several ways, including monetarily and related to research advancement. Finally, the PI agrees to provide the DSI with an abstract and optional image which will be used for promotional purposes including in the annual Seed Grant Showcase (annually in December).

Grant Details:

• Funding of up to $100,000 for projects spanning two years.
• Projects intending to pursue external infrastructure grants can apply for up to $200,000.
• The resulting datasets must:
  • Be accessible to all UMN researchers, where possible, or easily accessible with appropriate access provisions.
  • Adhere to university policies, especially those pertaining to Research Data Management: Archiving, Ownership, Retention, Security, Storage, and Transfer and Data Privacy. 
  • Expand upon or create novel data sets addressing current research gaps.
  • Be thoroughly annotated and cleaned as much as feasible.
  • Be available for upload to UMN-owned data repositories.

Eligibility Criteria:

• Faculty members and research teams from diverse disciplines across UMN are encouraged to apply. Faculty or research staff (P&A) with their primary appointment at the University of Minnesota throughout the UMN system are eligible to apply to be a faculty fellow. Adjunct or affiliated faculty are not eligible for funding under this program.
• Proposals must focus on the creation or expansion of data sets necessary for innovative research.
• Collaboration between multiple departments or research centers is highly encouraged.
• Plans should address how infrastructural challenges, such as data storage limits and costs, storage governance, and user access will be addressed.  

Application Requirements:

Interested applicants are invited to submit a proposal of no more than 5 pages, addressing the following:

1. Project Overview:
   • A clear description of the proposed project and its objectives.
   • High-level explanation of the data set and possible research areas it could be used for.
   • Relevance to one of the five MnDrive areas:  Robotics, Global Food, Environment, Brain Conditions, and Cancer Clinical Trials, if applicable
2. Significance:
   • Discussion of the importance of the proposed data set for advancing research in the relevant field(s).
   • Identification of current gaps in available data sets that the project aims to address.
3. Methodology:
   • Detailed plan for data generation, expansion, annotation, and cleaning.
   • Explanation of the steps to ensure data accessibility, privacy, and compliance with applicable UMN policies .
4. Data Repository: 
   • Description of the proposed UMN-owned data repository for hosting the resulting data set(s).
   • Plan for data sharing and accessibility within the UMN research community.
5. Budget and Timeline:
   • An itemized budget outlining how the funds will be utilized.
   • Proposed timeline and milestones for project execution and completion.

The DSI is committed to supporting the creation of high-quality data sets that drive groundbreaking research across the University of Minnesota. We encourage innovative proposals that push the boundaries of knowledge and contribute to the advancement of data science and related fields.