Introducing Speed - the latest attribute addition to our dataset. This map illustrates speed, and what it means for what you can do with our data.
Whenever we introduce a new attribute into our dataset, we do so with the ambition that our customers will find even more utility from our data. Today we are introducing speed as a value, paving the way for applications across all manner of analytical use-cases.
Speed can help us look beyond where consumers go - and into what they are doing there. One single datapoint in isolation can mean almost anything. Add a place name or category, and we can know something more, but only in the sense that the place was an origin or a destination for the consumer. Where the points in between are concerned - ie. when in transit - there’s much less to go on, but we still have questions to ask. How were they travelling? Which way were they going? How long did they spend there and what therefore does it mean to them?
Heading, coordinates, timestamp, elevation, accuracy and even acceleration are all attributes that are freely available to software providers through the mobile OS;
LocationManager in the case of Android, and
CoreLocation in the case of iOS. Other geographic attributes, including speed need to be inferred. We all remember our school-era maths; S=D/T.. right?! Well, yes - but perhaps one reason that speed is not available as an attribute from the OS is because the location component (that informs ‘distance’) is so jittery, the maths would often claim you’re travelling at 0.00001 ; or faster than the speed of light.
Yes, it sure does. As part of our comprehensive data resolution methodology, we normalise the speed attribute to tame the peaks and troughs - smoothing out the anomalies in order to arrive at their more likely and representative values. Check out the interactive map below, which thanks to our friends at Carto brings this fabulous new attribute to life in all of its mesmeric glory.