Many research projects, in a wide range of disciplines, can benefit from data science.  MIDAS provides support for U-M investigators to improve the data science component of grant proposals in many different ways, ranging from a simple description of MIDAS facilities and resources to substantial collaborative research.  Inquiries should be sent to:

  1. For MIDAS facilities and resources, please submit this Google Form to access the boilerplate language.
  2. For a Letter of Support, please include, in your request, a draft abstract of your proposal and whether you seek specific types of support from MIDAS. Please send your request to MIDAS at least one month before the U-M internal deadline, so that we have time to work out the support details and to iterate the letter as needed.  
  3. To find data science experts to give you feedback on the data science portion of your proposal, requests should be sent to MIDAS at least one month before the U-M internal deadline, and the proposal should be in near-final form.
  4. At the proposal planning stage, MIDAS offers an overview of data science research resources on campus and will help connect the team with data science collaborators. When we receive this type of request, a MIDAS team member will start the initial conversation and coordinate appropriate follow-up discussions.  Even with our help, it may take you some time to determine the suitability of a resource you were previously not familiar with. Also, good research collaborations take some time to develop.  For these reasons, we recommend that you contact us as early in your planning process as possible, ideally several months before the deadline.

We may be able to help in other ways, not listed above.  If you seek other types of support, we encourage you to contact MIDAS as early as possible to initiate a discussion.


2019 Propelling Original Data Science (PODS) Grants

A primary mission of the University of Michigan Institute for Data Science (MIDAS) is to foster innovative and groundbreaking multi-disciplinary research in data science.  MIDAS is pleased to announce our next round of funding for innovative data science.  MIDAS plans to fund research in the broad area of data science, including: 

  • Developing the theoretical foundations of data science;
  • Developing data science methodology and tools;
  • The innovative application of data science methods in any research area;
  • Examining and managing the implications of data science for society and the public interest;
  • Especially encouraged are proposals that combine a data science methodology component and a clear research question.

We are particularly interested in funding pioneering work based on innovative concepts that promises high reward, major impact, promotion of public interest, and potential for major expansion.  In other words, we aim to fund “disruptive” instead of incremental research.  All projects should be collaborative and interdisciplinary, with faculty from at least two departments/research units identified as PI and Co-PI(s) respectively.

Award Information: 12 – 15 projects will be awarded for a duration of 12-18 months, based on a competitive process.  Two levels of funding are available: 1) $30K, MIDAS will provide 100% of the funding, with no cost-share required.  2) Up to $90K, with cost-share above the first $30K in the ratio of 2:1 (MIDAS:Investigators or their units). For example, if you request $60K, your cost-share portion will be $10K and MIDAS will provide $50K.  Please email  for questions regarding the cost-share.

Who May Apply: Principal Investigators (PIs) and co-PIs should be faculty members at the University of Michigan (Ann Arbor, Dearborn, or Flint campus), and should not have been a  PI or co-PI of a previous MIDAS grant.  An individual may participate as PI/co-PI on only one proposal. Co-investigators, consultants and other personnel are not limited by this restriction. 

Important Dates:

  • Sept. 10, 2019: Submission of PI name(s) and tentative proposal title (Pre-submission)
  • Sept. 20, 2019: Proposals due (Proposal Submission), before 11:59 pm.
  • Nov. 15, 2019: Awards announced
  • By Jan. 1, 2020: Projects start

Proposal Content:

  • Project description, up to 4 pages, in Arial with minimum font size 10.  This should include Specific Aims, background, significance and innovation, and methods.  Most importantly, a description of why this project is “pioneering work based on innovative concepts that promises high reward, major impact, and potential for major expansion”.
  • A transition plan (up to ½ page) that describes the strategy for follow-on funding and activities, such as the next phase of research, curriculum development, data products and/or commercialization.
  • A Statement of Societal Impact (up to ½ page) that describes how this project will benefit the society, and, if any, potential negative impact that needs to be carefully avoided.
  • References (no page limit).
  • Two-page biosketch in NSF or NIH format for PI, co-PI and senior personnel;
  • A detailed budget and budget justification.  A generic budget template is available, but you can use any budget template that you prefer.
  • If cost-share is applicable, include proof that you have secured it (e.g. a letter from your department chair).

Review criteria

  • Innovative concept and/or approach;
  • The significance of the research questions;
  • Multi-disciplinary collaboration;
  • Likelihood of success;
  • Impact to the research field;
  • Broad impact to UM data science research community.
  • Potential for continuation, external funding and/or commercialization.

Post-award expectations

  • PIs, co-PI’s and senior investigators are expected to become MIDAS affiliate members.
  • All teams will be expected to present at MIDAS events and participate in MIDAS activities for data science research, education and community building. 
  • All publications, public presentations and products from this award should acknowledge MIDAS.

For questions, please contact:

Data Acquisition for Data Science (DADS) supports acquisition, preparation, management, and maintenance of specialized research data sets used in current and future data science-enabled research projects across U-M.

DADS is funded through the Data Science Initiative (DSI); total funding is capped at $200,000 per year for 5 years.

DADS will be managed jointly by the Library and Advanced Research Computing (ARC), with support from ARC’s Consulting for Statistics, Computing, and Analytics Research (CSCAR), MIDAS, and ARC-Technology Services (ARC-TS) units.

Requests for DADS funding will be submitted through a web form available on Library, MIDAS, and CSCAR websites, and accepted on a rolling basis. Selection criteria and processes are detailed below.


  1. Relevance/importance (merit, extent of user community, etc.)
    1. DADS requests will be reviewed on their scientific merit and potential for impacting data science-driven research across the U-M Ann Arbor campus.
    2. Data sets acquired through DADS should have the potential to serve a wide segment of the U-M community.  Highly specialized procurement requests that only serve individual researchers are discouraged.
  2. Costs (product/license and ingest/processing)
    1. DADS funds can be used to pay licensing and acquisition fees to publishers and commercial data providers, potentially including one-time or subscription-based costs.
    2. Data acquired through DADS can be processed into analyzable form by CSCAR or other U-M personnel; DADS funds can cover the costs for this data processing.
    3. Requests can be made for DADS funds to be used to cover transfer, processing, and storage costs for data that are otherwise free to obtain (e.g., to mirror open data repositories or to aggregate data obtained through an open API).
  3. Usability (ease of use, analytical tools, documentation, etc.)
    1. Data sets acquired through DADS should be made available to the U-M community through Turbo Research Storage or other campus storage options.  Costs for use of these services can be covered through DADS.
    2. Priority will be given to data made available with appropriate documentation and metadata.   [Note: If the raw data are subject to processing, the raw data will be retained and all scripts needed to generate the processed data will be made available along with the data.  Metadata pertaining to the raw data, and documentation describing any data processing that was performed will be preserved and made available along with the processed and raw data.]
    3. Since the data are intended to be used by multiple researchers, there is a strong preference to use open and well-documented data format standards.  If the data are provided in a proprietary or unusual format (e.g., SAS or MS-Access data files), CSCAR can be contracted to convert the data to an open format.
  4. Restrictions (embargo, number of users, exclusive use by single requestor)
    1. Priority will be given to data made openly available to U-M researchers, possibly within the constraints of dataset license and data use agreement.
    2. DADS funds should not be used for data management pertaining to new data produced at U-M.
    3. Restricted data, e.g., in which each user needs individual permission from the data provider to access the data, is eligible for this program provided that there is a clear process for additional users to obtain access.


To request funding from DADS, fill out this form. Requesters will be asked to provide:

  1. Description of data set: domain, size, format, metadata and documentation, licensing and usage restrictions, raw or processed, required analysis tools, etc;
  2. Data source: vendor, publisher, foundation, government, web, research, etc;
  3. Intended use and community: requests must indicate the community of users that can be supported by the data resources while maintaining licensing, security, and other data restrictions as outlined in any applicable license or data use agreements;
  4. (if applicable) Data processing requirements;
  5. (if applicable) Hosting preference (Turbo, etc.);
  6. Estimated cost for acquisition and steps 4-5.

Requests will be accepted on a rolling basis. Questions can be directed to  Unit-specific questions can also be sent to:

Library: Catherine Morse, 

CSCAR: Kerby Shedden, or

ARC-TS: Brock Palen,

Requests will be reviewed by a DADS committee comprised of Library and ARC personnel.

Below is a selection of grants possibly relevant to data science researchers. MIDAS and the other units under Advanced Research Computing can provide technical and other assistance for U-M researchers interested in applying for grants. Please email for more information.