Overview


The University of Toronto’s success in achieving its twin mission of excellence in education and research depends upon the institution’s ability to collect, access, and analyze a variety of institutional data. Such data are valuable assets to be leveraged and governed responsibly. The goal is to support the accuracy, accessibility, transparency, analytical quality, and timeliness of evidence-informed decision making at the University.

The University of Toronto is in the early stages of developing an Institutional Data Governance Program. A good data governance program provides structure, processes and organization needed to guide the collection and management of data (i.e., the data asset). Design of the program will be guided by a data governance committee. The committee will begin by developing a data governance framework. The framework requires consideration of the scope of the program, the definition of data governance as it applies to the University of Toronto context, and a set of guiding principles. Ultimately the committee aims to create a set of companion guidelines which outline the rules, the roles, processes and programs at the University.

The University of Toronto data governance initiative sits within the broader context of the Institutional Data Hub, which includes initiatives in data governance and business intelligence. A separate business intelligence committee have been established to work alongside the data governance committee.

The Data Governance Committee has articulated five pillars of data governance; working groups will be established around the first three pillars, while the last two pillars – quality and integration – remain outside the scope of the committee at this time:

Retention Project Pilot

The data governance committee has chosen the Retention and Graduation Rate Analysis Project as a pilot to inform the work of the committee. The work of the data governance committee will evolve and adapt as it works through the pilot project.