Modern sensors are ubiquitous, enabling a flood of data to be collected by devices ranging from smartphones to cars and from smart inhalers to tractors.
But collecting data is just the start. To be useful, it needs to be turned into information that changes what we do. That’s where visualising data in an intuitive way can help.
Running sophisticated analytical algorithms on the latest processors or in the cloud lets us uncover interesting behaviours and present it in an engaging way.
Every day the London Underground carries more than four million people between 270 stations – every journey creating a piece of data.
Our analytical approach turns passenger journey data on its head to give insights into traffic patterns. An algorithm combines stations with similar traffic patterns into clusters.
The result is an interactive map of the London Underground overlaid on the familiar canvas of Google Maps. A visualisation not of the data – but of the analysis of the data.
Users quickly see some things they expect – commuter home, work and transit stations, and the traffic flows from outer to inner London in the mornings.
But the visualisation also reveals geographic anomalies – such as Uxbridge being a work destination – and unexpected clusters, such as ‘social’ destinations around cinemas and theatres.
In a second visualisation they can play ‘what if’ – visualising closing stations and diverting tens of thousands of commuters at the tap of a finger.