Collaborative Research Teams

Data science is defined as the science of collecting, manipulating, storing, visualizing, learning from, and extracting useful information from data in a reproducible, fair and ethical way. Data science is inherently interdisciplinary and building capacity in data science has the potential to advance research frontiers across a broad spectrum of fields. Entirely new fields of data science are forming at the intersections of traditional disciplines and foundational fields. The model of the University of Toronto Data Sciences Institute (DSI) has been developed to make it easy for researchers to find each other, foster research connections through the research supports it provides for Collaborative Research Teams (CRTs) in emerging fields and encourage work in the foundations of data sciences themselves.

What is a CRT?

To be eligible to apply for DSI funding, scholars must assemble a collaborative research team (CRT). Our CRTs bring together expertise from across disciplines to form multidisciplinary teams composed of faculty from at least two different U of T divisions (or external partners) who are focused on the development of new data science methodology or the use of existing methodology in innovative ways previously not considered, or not possible, to address questions of major societal importance.

CRT Eligibility Requirements

  • Members of a CRT that have an affiliation with U of T must be members of the DSI.
  • The PIs of the CRTs must have their budgetary appointment at U of T or at a DSI Partner Organization/Institution. DSI Partner Organizations/Institutions can be found here. Co-investigators can be appointed at any institution.
  • CRTs can be new or existing research collaborations. CRTs are cross-disciplinary research teams composed of, at minimum, two PIs from different U of T or external partner divisions.
  • At least one PI must be a computational or data scientist. A computational or data scientist may include individuals working in foundational data science disciplines, such as statistics, mathematics, engineering, information sciences, and computer science, or individuals engaged in big data-driven research, such as computational biology, computational social sciences, or digital humanities.

This is not an exhaustive list of fields. Applicants may provide alternative descriptions for their role as computational or data scientists in a CRT, if applicable.

Funding

  • CRTs are supported through application for funding, including Catalyst Grants, trainee positions, and supportive infrastructure.  
  • Annually, the DSI launches calls for CRTs to apply for Catalyst Grants.
  • Annually the DSI launches calls for CRTs to apply for trainee support.
  • CRT funding proposals emphasize innovative application and/or novel development of computational and statistical methodology.  
  • A proportion of Research Catalyst Funding is earmarked for research in a DSI Thematic Program while the remaining research funding is available for CRT projects which may not necessarily fall under these themes.