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  • Data & Democracy Initiative

    Data Science Institute (DSI) Data & Democracy – Autumn 2021 RFP

    Funding for the development of new data-driven research that can lead to effective interventions to mitigate misinformation and censorship online and barriers to political participation in the digital age.

    Application Deadline: Monday November 29, 2021 by 11:59pm CDT

    Decision Notification: Mid-December, 2021

    Earliest Project Start Date: January 3, 2022

    Project Funding Levels – Exploratory Grants, Up to $15,000; Signature Grants, Up to $65,000

    DSI Data and Democracy RFP_FY22

    Apply Online

    The Data Science Institute (DSI) in collaboration with the Center Effective Government (CEG) is pleased to announce a call for research proposals focused on the intersection of democracy, public policy, technology, and data science. 

    The goal of this program is to 1) encourage new collaborations between departments and units across the University of Chicago campus, 2) provide unique educational experiences for students, and 3) position our institution to be a world-renowned center of research on political participation and freedom of expression in the digital age. Projects supported by this call will be part of an ambitious three-year research initiative focused on freedom of expression and political participation in the digital age. 

    Collaboration Event (11/5/21)

    Potential applications are highly encouraged to attend a collaboration roundtable event on November 5th from 2-3pm to meet new collaborators and share their research ideas. This is a low stakes event and an opportunity to hear more about what projects we are likely to fund and meet potential collaborators. Researchers are encouraged to attend this event even if you do not have a fully formed idea for a research project. Register for this event here. 

    Overview

    Projects may focus on broad and cross-cutting topics such as, but not limited to:

    • Online freedom of expression: How does the consolidation of online platforms impact free speech? What are the implications of online disinformation, censorship and information control strategies on offline actions like polarization, voting, and distrust in government and institutions? 
    • Political participation & technology: Democracy and political participation has historically included some groups and marginalized others. What are data-driven strategies to better understand how democratic processes encourage or discourage political participation. Proposals with a particular focus on mitigating barriers for marginalized groups to participate in political processes are particularly encouraged. 
    • Democratizing data: How do larger groups of people (civil rights groups, etc.) interact with government data, particularly without “deep data expertise.” How do we make data more accessible? 

    Funding

    Research funding is available for exploratory awards (up to $15K), early-stage projects, or signature projects (up to $65K) which provide resources for more mature projects. 

    Eligibility 

    • Principal Investigator must have PI status at UChicago. Please find more information about UChicago PI eligibility and policies here
    • Each application must have at least one PI from the University of Chicago and at least one co-PI from a different unit within the University of Chicago (e.g., departments, divisions, schools).
    • Applicants may submit more than one application, with the same or different collaborative teams, provided that each application is scientifically distinct.

    Application Requirements

    • PI CV or biosketch
    • Abstract (250 words max): What is the problem you seek to address, what is your approach to address this topic and what specific outcomes will your project deliver? 
    • Research Plan (2 pages max, excluding references): Please describe your research idea and why it is important, why this work requires collaboration, how this proposed work will be done and anticipated outcomes, research timeline & milestones, and the specific follow on funding opportunities you will target should the project generate expected data, analysis or results.
    • Budget and Budget Narrative (a budget template is available for download).
    • Optional Supplementary Materials: Applicants may upload supplementary materials, such as references, diagrams, images. The supplementary materials should not be used to circumvent the page limitations.

    Review Criteria

    Proposals will be reviewed by a faculty committee using the following scoring rubric: 

    • Intellectual Merit: Advances research innovation in the field of data science and the social sciences (“domain field”). Projects should include a collaboration between computational researchers and social scientists; projects should avoid providing a service to either domain.
    • Impact: Data Science research and solutions driven by a specific and compelling societal problem; approach delivers impact with both breadth and depth. 
    • Interdisciplinarity: Includes collaboration between two or more disciplines as appropriate to solve the problem area. 
    • Scalability: A clear plan to leverage seed grant support to attract additional funding sources to support the project’s long-term efforts beyond the 12-month project period. 
    • Feasibility & Deliverables: Rapid ability to produce research, data, tools, software or other results within the project period. 

    For any questions about this opportunity, please contact data-science@uchicago.edu. We look forward to your application.

    Terms & Conditions

    Funding Usage: Award funding cannot be used for faculty salary support, course reduction, academic leave, or summer salary, external (non-UChicago) collaborators; the purchase of equipment at institutions other than UChicago, or indirect costs.

    Reporting: The PI is required to submit a 6 month progress report (“Progress Report”) and 12 month final report (“Final Report”). Final Report templates will be provided for your project on the Funding Opportunities portal (http://fundingopportunities.uchicago.edu/) and can be completed at any point before the deadline.

    Acknowledgement: All publications and presentations resulting from the work supported by this award should carry the acknowledgement: “Supported with funding by the University of Chicago Data Science Institute.”

    Initiative Participation: One of the goals of the research initiative is to build an active community and grantees will be requested to participate in community activities. Activities may include evidence workshops, presentations, conferences, and other relevant activities. 

  • Seed Funding

    Early-stage ideas are often too risky for traditional funding sources and require support to demonstrate feasibility and preliminary results. This is particularly important for projects that are interdisciplinary, ambitious, and expand the boundaries of existing scholarship.

    CDAC Discovery Grants

    Discovery Grants provide risk-tolerant seed funding for innovative data science projects intended to achieve a clear impact on major scientific, scholarly, and societal questions.

    Grant recipients will also benefit from a suite of resources designed to help projects scale:

    • Identification of follow on funding: assistance in developing customized, long-term plans for securing external funding in subsequent stages of the project.
    • Interdisciplinary networks: access to our network of academic, civic, government, and industry connections.
    • Community: engagement with the University data science community and beyond, through quarterly receptions for all grant cohorts, workshops, and speaker series.
    • Communications: amplification of research results through our website, news articles, and events.
    • Student & technical talent: identification of talented students through our summer internship program and access to technical staff.

    Visit our research page to learn more about our project’s investigators, outcomes, and discoveries.

    Our Autumn 2019 cycle has closed. We will announce the next call for CDAC Discovery Grant proposals in Autumn 2020. Join our mailing list to receive information about the 2020 application process. You can review our most recent RFP here

    AI + Science Grants

    Research funding for AI + Science research projects among the University of Chicago, Argonne National Laboratory, Fermi National Accelerator Laboratory, and Toyota Technological Institute at Chicago. You can review our most recent RFP here to learn about upcoming deadlines.

    Visit our research initiative page to learn more about our project’s investigators, outcomes, and discoveries.

  • Discovery Challenge

    Update 10/29/21: This program has closed. Please visit the Data Science Institute website for active and future funding opportunities. 

    CDAC Discovery Challenge

    The Discovery Challenge is a seed funding program at the Center for Data and Computing (CDAC) that accelerates the research-to-impact process through the development of research-based, use-inspired data science technologies and tools. It focuses on cutting-edge data science and AI research and solutions that can be developed and piloted on a short timescale. The Discovery Challenge also requires the inclusion of external collaborators from industry, nonprofit organizations, or other external stakeholders that can provide critical input and accelerate the transition of research into practical use.

    Program Goals

    1. Accelerate the development of transformational AI & data science research and technologies that deliver high impact results to society,
    2. Deepen cooperation and information sharing between potential end users such as industry, government entities, nonprofit/civic or healthcare organizations
    3. Position projects to successfully scale and secure future large-scale sponsored research funding.

     

    Why This Challenge?

    The guiding rationale of the Discovery Challenge is that societally relevant research requires engagement with experts across disciplines– as well as multiple kinds of stakeholders, including the end users of such outputs. However, identifying, engaging with, and creating solutions for interdisciplinary challenges that also benefit (and don’t inadvertently harm) stakeholders is a non-trivial task that often requires matchmaking, stakeholder engagement, and a plan for coordination.

    In addition to seed funding, project teams will become major research initiatives at the Center for Data and Computing, benefiting from access to CDAC lab space, computing resources, corporate engagement, and technical research staff.

    For more details on the FY21 opportunity, visit the Discovery Challenge hub and contact Julia Lane (jlane2@uchicago.edu) with further questions.

  • C3.ai DTI

    C3.ai Digital Transformation Institute

    The University of Chicago is one of six universities joining with Microsoft and C3.ai in this new consortium for accelerating artificial intelligence innovation and advancing its benefits for business, government, and society. CDAC helps UChicago scientists connect with each other and peers at the other partner institutions to create strong research proposals for DTI initiatives.

    The Institute’s first call for proposals focuses on using AI to abate the spread of COVID-19 and advance the knowledge, science, and technologies for mitigating the impact of future pandemics. You can read more information about this research award program at C3dti.ai.

    Matchmaking for UChicago researchers:

    If you have a potential project and need help identifying a collaborator at UChicago, please contact Julia Lane, Executive Director of CDAC, with a brief description of the project and research question of interest.

    You can also submit an idea to the UChicago C3DTI Team Matchmaking: Collaboration Inventory.

    • Complete the form to indicate interest in collaborating on a proposal to the C3DTI’s first call for proposals and to access the spreadsheet of all potential collaborators. This collaboration inventory is open to anyone with PI status from any of the universities that are part of the C3.ai consortium (University of Chicago, MIT, Princeton University, UIUC, Carnegie Mellon University).
    • UIUC also hosted a matchmaking event: for a list of projects, a recording of the webinar, and names of collaborators, please visit their wiki page.