ES | EN | PT


Every day 19 million trips are made within the metropolitan area of ​​Buenos Aires. People from all parts of the city and the most diverse socioeconomic realities move on the streets on their way to work, study, shop and a host of other reasons. In addition we add the trips that need to pass through the town on the North - South or South - North. Meanwhile, the transport system of the city is trying to cope with the demand and roads are collapsed by mix of private and public transport systems. How to achieve solutions in such a complex system?

Understanding how a system that has long ceased to be simple and linear works must be first step. A key part of this process is to have data on the system that allows to build understanding about it. Another one is to have the tools to analyze and process the data. Today, programming languages ​​such as R, Python and Javascript, or Business Intelligence tools like Tableau can search large volumes of information to extract the relevant and display them in a didactic and comprehensible manner, even for those who are not experts on the problem.

In BerecoLabs we believe that taking advantage of these tools enable us to understand complex systems in ways that traditional approaches don’t. As an example we turn a origin-destination matrix, a simple chart full of numbers, into a tool suitable for analysis and the spreading of ideas. The data used corresponds to the Household Mobility Survey of Buenos Aires (ENMODO) from 2010, which studied the socioeconomic characteristics and all trips done during a day by the members of 22,500 households in the region. The animation is built using Javascript using code based on the one created by Christopher Ingraham.

Number of trips by district and their use

Figure 1. Interactive infograph with the data of origin and travel destinations in the metropolitan area of Buenos Aires, press one of the districts to see an animation with flows of travel represented by the thickness of the lines drawn.

Having information with high spatial detail and frequently updated is essential to manage complex systems. Today the tools and technologies to generate information in a decentralized manner in real time already exist and using them properly would make possible taking better decisions when managing and planning the transport system.