Data for Good

The future is friendly when data is used for good

Data for Good is an 
, Privacy by Design-driven insights platform that gives leading public good researchers access to high quality, 
strongly de-identified data

Since 2017, this program has enabled safe, responsible innovation so that data can be used in ways to help you, your community and society at large - 
without compromising privacy
. In fact, privacy safeguards were a key consideration during the development of the initiative and have been a feature of the program since its inception.

In 2023, TELUS became the first company in the world to achieve
ISO 31700-1 Privacy by Design certification
for the Data for Good program, demonstrating TELUS’ commitment to safeguarding privacy and advancing the principles of trustworthy data practices across Canada and beyond.

Remarkable data outcomes for Canadians

Learn how using data responsibly has supported social good.

Data for Good solves problems that matter to Canadians

See what leading researchers have to say about Data for Good.
Are you a researcher studying a topic in one of our areas of social impact? Contact us at 
Data&[email protected]
"Unmatched network mobility analytics. These strongly de-identified insights allow us to study a range of important topics such as access to parks and greenspaces, and trends in home working."
Jed Long
Associate Professor in Geography and Environment, Western University
“Information and Privacy. Data for Good combines the best of two worlds. It gave us an opportunity to identify key locations to be used in transportation systems based on human mobility patterns.”
Borzou Rostami
Assistant Professor, Alberta School of Business - Department of Accounting and Business Analytics, University of Alberta
“The Data For Good program has provided us with anonymized datasets on network activity that allow us to explore with emergency response agencies whether predictive models can help anticipate emergency events and hence improve response and public safety.”
Alberto Leon-Garcia
Professor in Electrical and Computer Engineering, University of Toronto

Giving Back

A man and woman taking their dog for a walk around the neighbourhood.

Social Impact

Western University

Jed Long is an Associate Professor at Western University in the Department of Geography and Environment. His main research involves using geographic information systems (GIS) and other spatial analysis techniques in the study of movement. Specifically, Jed is interested in developing and applying novel methods for spatial and space-time analysis.
A man and woman taking their dog for a walk around the neighbourhood.

Social Impact

University of Alberta

The University of Alberta is using Data for Good to find ways to build efficient transportation in response to natural disasters.
Smoke escaping the smoke stacks

Social Impact

McGill University 

As Canada continues to invest in science and technology to help the country achieve its goal of
net-zero greenhouse gas emissions by 2050
, the
Data for Good program
and McGill University have joined forces to advance climate change research.

It's always your choice

It's important that you know the data accessed by researchers as part of Data for Good isn't actually about you. Rigorous de-identification and aggregation processes remove any personal identifiers, meaning that the data used is not personal data that can reasonably identify who you are, where you go or what you do.
Even though this is the case, you can always choose to opt-out of Data for Good.

Designed Responsibly: How Data for Good works

The program includes technical, contractual and procedural protections to ensure that strongly de-identified and aggregated network mobility data is used by authorized parties for approved purposes that are socially beneficial.
  1. Internal Review.  Participating researchers are reviewed for alignment with the program qualifications and 
    TELUS Trust Model
  2. Terms of Use. Data for Good requires strict adherence to our program agreement, which outlines the purpose for access, data retention, and prohibition on attempts to re-identify data.
  3. User Training. Researchers are provided with training regarding the applicable scope of the program, privacy controls and terms of use prior to onboarding.
  4. Platform Access. Once researchers are approved and trained, they receive access to a controlled API for network mobility data.
  5. Value. Through this access, the researchers can conduct innovative projects with a social impact.