The Data & Analytics Unit was established in 2019 as an expansion of the former Big Data Innovation Team to be a hub for data analytics, data science, data collection and data management. Its goal is to advance data practice and continue to tackle high-impact projects around Vision Zero, multi-modal travel, and emerging forms of mobility. The Unit is comprised of three teams: Data Operations, Data Science, and Data Collection.
The unit is dedicated to working in the open, and much of the code worked on is available in repositories prefixed by “bdit” on the City of Toronto’s GitHub Page.
If you are interested in the data used to analyze the performance of Transportation Initiatives, a number of the data sets used in the team’s analyses are available on the City of Toronto’s Open Data Portal.
MOVE is a collaboration between the City and Code for Canada. The Data & Analytics Unit is responsible for building and maintaining transportation infrastructure in Toronto, and data is foundational to this work. MOVE is a new tool that centralizes the city’s collision and volume data, and will enable the city to take a more proactive approach to decision-making and mobility in Toronto. More information can be found on their blog and an overview of the approach and lessons from the project is available on the Code 4 Canada blog.
Throughout 2020, the City introduced a variety of COVID-19 response programs in consultation with the Medical Officer of Health to accommodate the need for residents to be outside of their homes while physical distancing. These programs, including ActiveTO, transformed Toronto’s streets to support the city during the first summer of the pandemic. ActiveTO dedicated road space to facilitate active transportation for essential trips and physical activity and is highlighted in the Toronto Office of Recovery and Rebuild’s COVID-19: Impacts and Opportunities Report.
As part of the overall ActiveTO monitoring and evaluation strategy, the Data & Analytics Unit collected volume data, bike share data, and partnered with Park People and Clean Air Partnership – The Centre for Active Transportation to complete public intercept surveys. You can see the results of this evaluation in this staff report provided to City Council on April 7th, 2021.
The Data & Analytics Unit, in partnership with Municipal Licensing and Standards, has prepared analyses of the impacts of the vehicle-for-hire industry on the City of Toronto’s Transportation Network. The 2019 analysis covered the period from September 2016 (when Private Transportation Company services were first licensed) to September 2018. The 2021 analysis covers the period from October 2018 to July 2021: examining the period following the previous report and the impacts of the COVID-19 pandemic on the vehicle-for-hire industry.
The 2021 report can be found at: The Transportation Impacts of Vehicle-for-Hire in the City of Toronto : October 2018 to July 2021.
The Data & Analytics Unit was involved in deploying sensor technology to monitor the performance of the corridor and surrounding impacts. Reports and dashboards on the performance and impacts of the corridor can be found here.
Relevant Open Data Sets include:
This initiative ran from May 31 until July 26 which called on civic innovators, transit users, data scientists, designers, urban and transportation aficionados, citizens, academics and advocates to answer the question:
How might we use data, design and technology to make all Toronto road users, especially seniors, newcomers and school children, safer immediately, and enable predictive and high priority interventions in the future?
Over the 8-weeks, participants worked in teams or independently to develop innovative and data driven solutions to make Toronto’s streets safer for everyone today and into the future.
The team with the most promising solutions was awarded a cash prize and the opportunity to receive coaching and training at Civic Hall Toronto to further develop their idea side by side with City of Toronto staff. You can find more details at the Vision Zero Challenge Website.