Rethinking Rio de Janeiro's bike paths using data and scientific knowledge

08/11/2016 by

How about rethinking the entire bike lanes plan of a city using scientific knowledge and data from Twitter, from Bike Rental (Bike Rio - Itaú), from Mapeando (from, from citizens’ request through 1746, integrating it with our mass transportation network?

This is another example of how we, the PENSA Team, are using data. The responsible for this project was João Meirelles, who captured data from many different sources to design a new bike lane plan to better meet the need of our citizens. João used the following data sources:

  1. Twitter geocoded data: tweets from Twitter users to infer their domiciles and to identify groups by income rates;
  1. Bike rental data: to create an origin-destination matrix of bike travels, using algorithms to fit it in our roads and to calculate the number of trips per day;
  1. Data from Mapeando (a project by bike lanes requests by our citizens sent through a collaborative map;
  1. Data from 1746 (Call Center): bike lanes demand by our citizens requested using our call center (1746);

  2. Mass transportation data: used as a reference for our transportation network, in such a way that the new bike lanes should try to connect the citizens to our subways, and trains.

All this data were analyzed and compared to our existing bike lane plan.

As a result of this project, 95 new kilometers of bike lanes were identified and proposed by the PENSA Team, and accepted by the Rio’s Environment Agency. This new 95 kilometers of bike lanes will provide a better integration among our citizens and our city.

This is another project in which we, from BIG DATA: PENSA - ROOM OF IDEAS, listened to the citizens even when they were not speaking directly to us. This is the way we think governments should develop their projects: using available data and scientific knowledge to better answer people needs.

Check below to see the complete presentation:

Pablo Cerdeira is the Head of the Center of Technology and Society - CTS/FGV and the former Rio de Janeiro's Chief Data Office