Open data: the latest on the public distribution of bike-share data

Convinced of the utility and potential of publicly-available data, in the spring of 2013 JCDecaux launched a universally-accessible web portal providing data on the various bike-share systems it operates. Although the primary goal is to help stimulate innovation, open data also meets the need for free access to information, which has been the focus of many local and regional authorities, including the Paris municipal administration.

So what can be said about the implementation of this approach today?

EASY ACCESS

The data is free and easy to access via JCDecaux Developer.

Two types of data are available:

• Static data: by bike-share system, stations with their GPS location, their number of bike stands, payment terminal availability, etc. The data can be downloaded in file format or accessed through the API*.
• Dynamic data: by bike-share system and station, the number of available bikes, number of free spaces, etc. The data is refreshed every minute and can be accessed through the dedicated API*.  The user must simply enter their e-mail address to obtain the data.

*API stands for application programming interface, a set of functions providing access to the services of an application via a programming language.

MILLIONS OF POSSIBILITIES 

More than three years since the launch of the JCDecaux Developer portal, there are over 4,000 active accounts and more than one million data requests per day. The platform, initially launched in Paris with the Vélib’ scheme, now covers all of the bike-share systems operated by JCDecaux, opening the way for numerous projects to develop. 

In terms of possible applications, there are two different ways the data can be used:

Use of data in real time

Where's the nearest station? How many bikes are currently available? Where can I drop off my bike? Real-time data processing can answer these questions, and can be used to develop bike location and availability services, which usually take the form of websites or mobile apps.

Use of historical data sets

What are the peak times for bike rentals? Which stations generate the most traffic?  What is the ideal time to pick up a bike?  You need a large database in order to study user behaviour and build models for developing ever more precise and effective mobility services.

All of the stakeholders in urban service development, be they developers, users, local authorities or businesses, can therefore contribute on a daily basis to defining and optimising the city of tomorrow.