A new representation of our transport network shaped by metro data
We wanted to liven up the traditional maps of the Parisian underground system, in a way that better matches the reality of commuting.
PARIS NEVER SLEEPS
Millions of commuters travel through the city — one of the world’s top tourist destinations — on a daily basis. Therefore it is no wonder that the city’s backbone consists of its metro system, known for its density and round the clock affluence.
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.
A team of loyal Metropolitain travellers, the Dataveyes members were keen to visually represent the underground system and its dynamics in an alternative way, which would better show the true reality of a commute, through data.
This is why we created metropolitain.io
Metropolitain.io is 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 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). Other datasets about time between stations were provided by the start-up Isokron (who realized the Locomote App).
A series of distinct elements got us to work on this project:
WHY WE DID IT
Our passion for smart cities
We are fascinated by anything that revolves around the ‘connected city’. In other words, how data can help shape and challenge the visions that we have of the areas we live in.
Visualization precisely goes beyond the abstraction of data. It helps uncover actual meaning on our activities, our habits, our environments etc. Data visualization can connect the dots, make you comprehend information that sometimes you would not see from ground level.
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.
Our passion in User Experience
Besides we are keen to provide our audience with a genuine, innovative user experience. Since Dataveyes was created in 2010 we have done a lot of thinking around data in general and how it can be best represented.
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.
Our eagerness to challenge representations
This project was carried out by our R&D lab, which gave us the ability to “play around” with a level of flexibility we would not necessarily have when working on a client brief. Looking back, we seized that opportunity, by trying out representation modes we were new to, such as map distortions or 3D.
The challenge for us was clearly to make sense out of those new representation modes, by reflecting on how they would help the user understand the information better. We see Metropolitain.io as an experiment, an opportunity to learn new approaches along the way, see whether people engage with it, show interest or want to emulate/ improve our existing project.
The first version of Metropolitain.io raised a number of questions:
- Are those new representation modes efficients?
- How will the general public approach this 3D interface?
- What will be the most used functionalities?
We created a testing plan which allowed users to freely discover the application so we could assess how usable the interface was. Here are the results:
- The interface generated curiosity among participants.
- Users immediately seek to use the interface as a tool to answer practical issues such as finding out the time it takes to get from one specific station to another.
- After a quick learning period, participants understood the purpose of the application and expressed a need for more detailed analysis functionalities.
- Many users would have liked to merge the Crowd View and the Time Map, in order to see how crowd levels evolved during the day.
- 3D often generated positive reactions. However, most users kept the 2D mode in order to easily navigate on the map.
OUR APPROACH
Prototype First
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 was the first time we built 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.
We felt we had to prototype first, in order to determine how the datasets would carry information across and challenge our representations. The prototype really gave us the key to understanding the data and what we could do with it.
From data-centered focus to user-centered focus
From that point onwards, the challenge was no longer for us to understand the data but to help others see it too. The design phase enabled us to make that data come to life, make it usable, in a way that is both exciting and detailed. This translates into a variety of interaction possibilities, buttons, info-boxes etc. We tried to find the right balance between aesthetics and relevance, to design a visualization that would serve our user’s purposes.
It was the shift from a data-centred focus to a user-centred focus. In some of our client projects we would rather proceed the other way around, depending on the circumstances. We aim to always operate in a seamless, flexible fashion. This is due to the mix of skills within Dataveyes and our ability to work closely together to get the most out of data.
Interpenetration of conception and production
The interface naturally went through a series of modifications as the project progressed, as we tried to optimize the way we would represent data. The design phase came much further down the road, almost 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.
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