A visual and interactive experiment on the Parisian underground network
Métropolitain: a fresh outlook on Paris metro system through data visualizationpublished on 26/03/13 — lire cet article en français
What is Métropolitain?
Metropolitain.io is our latest experiment, led by Dataveyes’ very own R&D lab. The project attempts to visualize and make sense out of Paris urban data. The interface enables users to interrogate datasets around average journey time between metro stations, at any hour of the day, as well as the number of people touching in at each station.
The data around crowd turnouts was made openly available by the RATP (Autonomous Operator of Parisian Transports) a few months ago. Other datasets about time between stations were provided by Isokron, a fellow Paris-based start-up company.
This visualization offers to challenge the way we traditionally view our 2D metro maps. Métropolitain takes on an unexpected gamble: using cold, abstract figures to take the pulse of a hectic and feverish metropolis. The metro map is no longer arbitrarily dictated by the spatial distance between two points. By playing around with two extra variables – time and crowds – users can transform the map, view it in 3D and unveil the true reality behind their daily commute.
Why did we make Métropolitain?
The metro is a central component in the daily life of millions of Parisians. As a result, the official metro map conditions the very way commuters approach time, and space, as they tend to select their journeys based on the perceived smallest distance between two points.
We felt it was time to offer a different approach, taking advantage of the increasing open data movement. A new perspective standing on three pillars – distance, time and traffic – could only help us unveil a new way of representing the area and the reality of its accessibility.
It is time to think beyond the intricacies generated by the data deluge. The increasing amount of data made available around us gives us the raw material to approach and quantify otherwise invisible streams: transfers, communications, connections, interactions.... We did spend some time looking for relevant data that would shed a new light on transportation and which areas of Paris were most/least connected to the metro as a result of the network’s configuration.
We have the unique opportunity to create innovative interfaces that transform the data that matters to our city lives into interfaces. Those can help us understand our metro network, identify hot and cold spots and ultimately save time during our daily commutes. In a nutshell, unleash the power of abstract data to serve the public interest.
Last November, we had the opportunity to pitch our concept and approach to a local crowd, at the TedX Pantheon Sorbonne event. Following this first interaction, we were encouraged to develop this project further and share it with a wider audience.
How did we make Métropolitain?
We used data provided by both the RATP and Isokron, on the back of an API that allowed us to determine the average journey duration between any two stations, depending on the time of day and date. Contrary to the way we usually approach datasets, we started by prototyping straight away, without any thorough wireframing, and even before we knew what the datasets exactly contained.
We directly developed the interface in WebGL as we felt it was the most suited for our purposes. Using WebGL (through a Three.js library) was an exciting task. While we had used WebGL for a few internal projects in the past, this is the first time we build an interface out of it for the wider public to use. We feel that this technology really fulfils the potential of graphical maps to dynamically calculate complex 3D objects. Overall WebGL enabled us to break free from the performance issues contained in our usual toolkit (SVG + D3.js). Keep in mind, however, that we did use D3.js in the small charts displaying information about the specific stations a user selects.
The interface naturally went through a series of modifications along time, as we tried to optimize the way we’d represent data. The design phase came along much further down the road, pretty much at the end, in order to make the interface more user-friendly and engaging. This kind of all-inclusive project got our team to work in a very integrated fashion, beyond the traditional boundaries of coding, data mining and design. Looking back, conception and production were very much intertwined.
Going forward, get ready to hear more about Metropolitain.io: our data visualization will be exhibited at the next Futur en Seine Festival in Paris, next June.