Critical Investigation of Data Science Grant

*** Please note: The deadline for this call has now passed. Thank you to all the applicants and for your interest. The below information is being left up for reference.***

Overview

Value and Duration
CDN $10,000 for up to 12 months
Application Deadline
17 April 2025 23:59ET

Purpose

The Data Sciences Institute (DSI) is a central hub and incubator for data science research, training, and partnerships at the University of Toronto. Its goal is to accelerate the impact of data sciences across disciplines to address pressing societal questions and to drive positive social change. 

The DSI at the University of Toronto Mississauga, DSI@UTM, is a tri-campus initiative to encourage research activity in Responsible Data Science that includes grant support for research funding, training, and community-building. 

Data science has tremendous potential to inspire positive outcomes in the world; however, there are concerns about the ethical deployment of data science techniques and the ways that the effects of data science may reify inequities and biases. The promotion of data science requires a dedicated understanding of power within societies and knowledge communities to ameliorate negative, unjust effects. Data science is and will continue to restructure multiple aspects of our world and it is important to maintain a commitment to questions of power, inequity, responsibility, surveillance, justice, and harm to ensure that collecting, manipulating, storing, visualizing, learning from, and extracting useful information from data is done in a reproducible, fair, and ethical way. 

The DSI Critical Investigation of Data Science (CIDS) grant is designed to provide seed funding for scholars to engage in critical investigations of data science. Projects can vary in scope from analysis of specific data science projects and approaches to the articulation of potential harms in existing datasets and data science writ large. A variety of methodological and epistemological approaches are welcome, including critical analysis, social inquiry, phenomenology, qualitative investigations of lived experiences, content analysis, rhetorical approaches, and/or the creation or evaluation of models, datasets, algorithms, and other data science methodologies.    

Single applicants proposing projects applying a critical lens to data science techniques, methodologies, or effects can apply for this grant. Funds of up to $10,000 can be used by successful applicants to fund such projects. The DSI will fund at least five projects each year and will hold rolling calls until our annual funding is used. 

Applicants should be well versed in critical theory and ethics (defined broadly). Applicants should articulate the proposed goals for their critical project and elaborate on the proposal’s possible impacts on society, ethics, inclusion, and our understandings of power. Applications will be evaluated on their application of critical theory to data science projects and/or methodologies. 

Eligible expenses are to be consistent with the appropriate tri-agency guidelines for NSERC Discovery grants, CIHR Project Grants or SSHRC Insight grants, with the exception of laptops which should only be included in application budgets when required for project-specific purposes (as opposed to general research). Expenses should not include events unless the event has a methodological purpose that is central to the proposed project’s outcomes. Proposals should clearly describe what role all research personnel will play in the research project. Questions on eligible expenses should be directed to awards.dsi@utoronto.ca 

Successful applicants will be required to: 

  1. Present their research at a future DSI workshop or seminar. (The logistics to be supported by the DSI@UTM).  
  1. Applicants are encouraged to produce a public end product, including but not limited to white papers, policy papers, contributions to conference proceedings, or appropriate journal publications. 

In addition, awardees may be called upon to act as reviewers for future DSI awards competition. 

The DSI is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas. 

How to Apply

The award is open to applicants who meet the following criteria:  

*Faculty budgetary appointments for the University of Toronto are continuing, full-time academic appointments with salary commitments from a University of Toronto academic unit. 

Applications are submitted via the DSI Good Grants application portal.


Register an account and select “Start Application” for “Critical Investigation of Data Science.”


DSI Good Grants Dashboard

The application is divided into tabs; each tab includes a set of instructions and fields to fill out. These instructions are also highlighted below.


Applicants will need to complete the following fields.


Tab 1: Start Here

  • Title
Tab 2: Applicant Information

You will need the following information:

  • Name
  • Email
  • Institution
  • Division (if applicable)
  • Unit (if applicable)

Tab 3: Proposal

Abstract (maximum 150 words)


Keywords


Objectives (maximum 500 words): comment on the following:

Impact (maximum 500 words): comment on any of the following that apply:

  • Impact on the data sciences
  • Societal impact
  • Ethical impact
  • EDI impact (integrating EDI into research; EDI-related social outcomes)
  • Connections to research communities

Methods & Budget (maximum 500 words): comment on the following:

  • Critical approach
  • Explanation of how the development of the critique will provide a novel contribution
  • How will the funds be used to meet your objectives?

Figures & Supporting Material (maximum 1 page): upload a 1-page .pdf with figures and supporting material.


Unit Head Signatures: Please fill out the provided template, convert to .pdf, and upload the unit head signature for the PI.


Tab 4: CVs


Upload the PI's CV.


Demographic Survey


All DSI applicants are asked to complete a short Demographic Survey. If we do not have a response on file, the link to this required component will be included in the applicant's confirmation email.

The DSI will form a Review Committee to lead the review of all eligible proposals received by the submission deadline. Reviewers are asked to consider the following categories:

  • Project objectives and their potential impact on the data sciences.
  • If applicable, alignment with the DSI Thematic Programs in Reproducibility or Inequity.
  • The extent to which the development of the critique will provide a novel contribution.
  • The extent to which the project considers how to advance EDI in research and outcomes.

All application materials can be submitted directly onto the form. For unit head signatures, you'll require the following template:

Past Recipients

Ronald Buliung (Department of Geography, Geomatics, and Environment, University of Toronto Mississauga, University of Toronto): “Missing Disabilities: Studying the Representation of Disability in the General Transit Feed Specification (GTFS).”

Felix Cheung (Department of Psychology, Faculty of Arts and Science, University of Toronto): “A New Standard of Equality-Focused Analysis in Well-being Science.”

Jessica Gronsbell (Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto): “A critical discourse analysis of electronic health records-based computational phenotypes for sexual orientation and gender identity.”

David Nieborg (Department of Arts, Culture, and Media, University of Toronto Scarborough, University of Toronto): “Tracking global data flows in the app ecosystem.”

Patricia O’Campo (Unity Health Toronto): “Towards a Critical Data Science Practice in Public Health Centred on Equity.”

Amaya Perez-Brumer (Dalla Lana School of Public Health, University of Toronto): “Towards Data Justice: Peruvian Transgender Women-Led HIV Science Data Governance.”

Zahra Shakeri (Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto): “Evaluating Social Bias in Large Language Models to Promote Health Equity.”

Robert Soden (Department of Computer Science, Faculty of Arts and Science, University of Toronto): “Building Equity into Climate and Disaster Risk Models in the Himalayas.”

Katherine Tamminen (Faculty of Kinesiology and Physical Education, University of Toronto): “Critically Examining the Use of Generative AI Images and Visual Qualitative Methods.”

Further Information

For more information, please contact awards.dsi@utoronto.ca.