Next Stop: Big Data

time taken away from sleep, gym, or eating dinner with the family.

With public transit there is give and take. We can’t expect luxury, but what we can hope for is efficiency and not feeling like a sardine every single day. Think back to the frustration you’ve felt watching a bus go by because the schedule displayed a certain time, and your gullible-self thought you had enough time to grab a coffee before your morning commute. If that doesn’t sound familiar, perhaps the mental toll of a broken transit system had you debating moving to a part of town that had better public transportation options. If any of this is relatable, you are not alone. According to a recent Forum Research poll taken by 1157 Torontonians, amongst those who travel to work or school, almost two-thirds (60%) agree that the time they spend commuting reduces their quality of life[1]

We all agree that our mental health somewhat deteriorates from all the commute time, but one could argue that we should expect it living in the city. However, when commute times keep rising, doesn’t the city become somewhat accountable in coming up with better options for commuters?  Forum Research discovered that on average Torontonians commute 42 minutes each way, an 8% increase from 2013. In other words, the average commuter is spending more than 6% of their day in public transit, which is time taken away from sleep, gym, or eating dinner with the family.


Will that always be part of the norm with transit? Do we have to just accept cranky mornings in the office or fed up students who arrive to class late?

Not according to Dublin. Just last year, the Dublin City Council collaborated with local transport operators to improve roads, bus ways, and train paths using Big Data. “Traffic controllers can now see the current status of the entire bus network at a glance and rapidly spot and drill down into a detailed visualization of areas of the network that are experiencing delay. These insights and the interface allow visualization of the data give them an opportunity to identify the cause of the delay as it is emerging and before it moves further downstream. This approach can accelerate the decision-making process to clear congestion more swiftly” writes INFORMS (the Institute for Operations Research and the Management Sciences).

As happy as we can all be that this the start of a great solution, as Torontonians we can’t help but ask what strides Toronto is taking in the same department?

In 2015, the City of Toronto came up with a Big Data Innovation Team. The team essentially brings together practical analyses of transportation data to uncover solutions to the problems facing transit around the city. While larger projects like the smart neighbourhoods at waterfront are designing futuristic plans, the Big Data Innovation Team is taking more realistic steps to integrate technology and data meaningful into transit operations.

Metrolinx and private companies such as WSP and Parsons have acknowledged the importance of smarter systems. In a 2016 technical report published by Metrolinx they clearly stated that “smart [transit] systems are fueled by data, and new mobility services could thrive or fail on the richness of their underlying datasets” [2]. Metrolinx outlines plans for smart technology and improved transit systems but for the year 2041 [3] - That’s only 9 years before you can meet up with Officer K. In the meantime, as commuters we demand improvements and upgrades in our lifetime, not 20 years from now. If the simple task of purchasing a metro pass online takes 4 hours for our transit cards to update, we can’t really expect much in terms of smart transit.


According to the same Forum Research of 1157 citizens, more than half (58%) say that building more transit is the best way to relieve congestion. One-sixth (17%) say the best way to relieve congestion is building more roads, and another (16%) say that something else should be done to relieve congestion. All respondents are correct in their own respect.

Using Big Data, cities like Dublin have already started tracking where more transit is needed and how to clear congestion. By utilizing data that citizens willingly and consensually share, cities can react in real-time to events and trends in order to make more purposeful decisions and be rewarded the benefits on that day. A research study conducted by University of Toronto collected train speed data and pedestrian traffic data using a smartphone [4] - this shows us that the very phone we use daily to scroll through memes and update our social media status’ can be used to analyze our cities’ transportation needs. This alone can change your commute time and your mood for that day.


While we’ve started the path to resolutions for the city, as urban dwellers we would also like to be in the loop. As much as the Big Data Innovation Team can update their website with new findings, being able to apply the information to our day would be far superior. Our personal data can act as a proxy for our voices and a way to help the city better understand and assess demand for certain services. Cities around the world are grappling with ways to collect and analyze data from commuters and often resort to purchasing data from third parties that aggregate data from the apps and services we use. Personal data that is repurposed for transportation planning poses “issues of ownership rights, privacy and costs associated with acquiring data” and even after obtaining such data, “the information available may not contain all the desired attributes or may not be structured in ways that are easily compatible with established methodologies” [5].


Opportunity to improve small things around us like our transit systems can lead to smarter and healthier cities alongside the overall mental health of the people within our communities.