The Fabrique des Mobilités Québec team is continuing its series of interviews in an attempt to become aware of the path of data, its value, and to learn how it is used for different purposes.
This article will allow you to learn more about the stakes of data collection, as well as Savoir-Faire Linux’s actions and obstacles to value and collect data. In addition, you will also discover the benefits of using this data for all parties involved: citizens, municipalities, and organizations.
Thanks to the funding of Montréal en Commun, the smart cities component led by the Montréal Urban Innovation Lab (LIUM), La Fabrique des Mobilités Québec supports sustainable mobility experiments like the one of Savoir-Faire Linux to extend the possibilities of the curb.
Collecting data: a complex task
Sébastien: In your experience, what are the main issues and challenges related to the curb in Montreal?
Larbi Gharib: One of the first issues that we have understood, while meeting with different mobility actors interested in the use of parking mobility data, is the lack of a consistent data structure. The data are in different types of formats, are not up to date, are sometimes not even available. There is also the lack of an existing ecosystem that allows the different actors to follow proper practices in the development, the organization, the updating or the monitoring of this data.
There is also an issue and a challenge with regards to parking: the issue is parking spots and the problem is to reduce them. Since our priority is to use alternative sustainable modes of travel to the car, we are trying to reduce the number of parking spaces in order to clear the lanes and allow bicycles and buses to pass rather than vehicles. Afterwards, the challenge is actually to account for these spaces and to optimize the amount of space used by these areas. Sometimes the spaces are not occupied by cars; they are dedicated to cars but something else could have been put in their place, temporarily. The issue is really the management of this area.
And then, the data today. The parking and mobility data that interests us in our experiments at FabMob is that which relates to mobility. And all this information is data on the movement of people, individuals, but also on the city’s and country’s infrastructures. This can be sensitive material, because a person can be traced, but also because the data quickly reveals the vulnerabilities of our city’s infrastructure.
Data valuation and collection methods
Sébastien: What work is done at Savoir-Faire Linux to value data and why is it important to do so? Can you also tell us where you collect data and in what format you collect it?
Larbi Gharib: It’s quite simple; we started by looking at the open data of the City of Montreal. It’s a website, a platform on which the City of Montreal makes available several types of open data, including the information on street signs. This is a sign that allows us to know if we have the right to park or not. This data is available in the form of different files in spreadsheet format. We have a file that gives us the signs, the list of signs, their position and a code that is associated with these signs. This code also tells us on the other hand what type of signage it is: is it legal to park or not? On the right, on the left? From what time until what time? We take this information and then we convert it. So that’s to answer the question of the origin of the data. This is the major source that we have used up to now. But we want to go and get data from other sources as well, in order to enrich the entire system.
The second part of the data sources for the project comes from car sharing data, such as Communauto data. This is data on the location of drop-off or pick-up points on streets and alleyways, or in private parking lots, in public parking lots. We have retrieved this data from a Website created by Communauto, which makes xml files available. This is a file format that allows us to structure data. It is available for Montreal, Quebec City, Gatineau, and several cities where Communauto is based in Canada.
There are also parking spots for electric vehicles, which are a slightly more precise, and which are available on the Montreal Electric Network website. And finally, there are other data: Bixi data, the location of Bixi stations, with the number of spaces, which allows us to give the length of the space occupied by Bixi parking lots. And also, the construction data, but that’s the only data we haven’t been able to get our hands on yet. This is the data that would really allow us to have a better understanding of the real time curb parking data in Montreal.
Sebastien: Before we talk about what you do with the data, what are the impediments to your work with curbside data?
Larbi Gharib: The first limitation is the quality of the data. Not all data is structured, as we said at the beginning, in the same way. And even in certain files, for example the parking data file of the city of Montreal, the signs data, the dates used to indicate the type, the regulation periods, for example from Monday to Friday, from December 1st to March 1st, the way of writing these regulations is not the exact same. And this information creates an obstacle in our work. We need to identify all the ways in which these regulations are written in order to have structured and accurate data at the end of the process.
The second obstacle is the lack of knowledge of the different sources of data. We don’t always know who to approach. For example, for signs, we discovered that the sign data comes from a sign ordering software that allows us to have the signs. So there is no exact tracking of the history of each sign installed by the boroughs. The districts will order signs and that’s how they know what signs they actually have. And also, there are labels put on the signs, so the actual data on the signs may not be the same as what we have on the City of Montreal’s open data file. We can validate it, it’s a massive job, which we can do eventually. But this is also one of our obstacles.
Sebastien: What can we do with this data and what benefits can citizens get from it? Are there any examples of use cases for this parking data?
Larbi Gharib: One of the use cases that we are trying to improve as we script and research the data is understanding the availability of parking spaces in the commercial street of Plaza Saint-Hubert. We set up a map that allows the user to see the parking spaces at any time of the day, throughout the week. This way, the user can know, before leaving home, if it is more interesting to postpone, to take his vehicle to park, or to take an alternative way because there is not much available parking at that time of the day. This is a practical case of the use of this data. But it can also be used in real time to know if you are allowed to park where you are parked with your vehicle, without leaving your vehicle to check the signs on the street and move along the street to try to find the information. It’s about getting an answer fast on the map or on an application. The data is being fed back to the user from the signs, to tell them whether or not they are allowed to park in the exact location they are in. This is a way for the citizen to use this data.
Sébastien: Do you see an added value for the City, for municipal organizations?
Larbi Gharib: Oh yes, for the City, the municipalities, the districts, it is even more valuable. By mastering the history and quality of their signage and the various stakeholders on the street curb, there can be better management of the area. It can allow the use or not of a part of this area for activities that can punctuate the year, such as the closing of a street for a particular event, for snow removal, for all the activities that the City must manage. And to have a data that is constantly updated, clear and easy to read allows us to reduce costs on all the aspects we mentioned, whether it is snow removal or development. For urban development management, this is a very useful tool and a very important piece of data. There are other businesses that can use this data as well to run their operations.
This interview raises important possibilities for the use of data in the Montreal curbside environment. Collaboration between citizens, municipalities and organizations, supported by experimentation, could maximize the use of curbside.
Stay tuned for more interviews on curbside!