Since we're on the topic of large-scale data collection, I thought some of you may be interested in Uber Movement's new "Speeds" product.

First launched in 2017, Uber Movement aggregates anonymized data from their ride-sharing business to create data sets and tools that can help cities make better transportation decisions.

Below is a (hex cluster) map of Toronto showing average travel times from downtown. I dropped the pin at Toronto City Hall. What is shown is the average for all days of the week during the month of January 2018.

Uber Movement's new Speeds product looks at how specific streets are performing relative to their "free-flow speed." Uber defines this as "the average speed of traffic in the absence of congestion or other adverse conditions." (The 85th percentile of all speed values.)

As of right now, Speeds is only available in 5 cities: New York City, Seattle, Cincinnati, Nairobi, and London. Here is a snapshot of London during the same time period as above, January 2018:

In comparison to what we were talking about yesterday, I have few concerns with the fact that my Uber rides around town have likely contributed to these mappings. With these use cases, the value really only emerges once you aggregate the data.