Metro maps can give you a lot of information about how best to traverse a city. They show the network’s extent, and how regularly metros and trains stop. Once you add other factors – like, say, station and carriage temperature, or regularity of service – into the mix, they can tell you even more about comfort and ease of travel.
But a map created by an internet user pushes station-by-station information to a whole new level. User Congosto built a map of Madrid’s subway on mapmaking site CartoDB, using a dataset of customer complaints to visualise problems on the network. Nested circles on each station are colour coded to represent the type of complaint, and sized to reflect the number of complaints made. This adds up to a very pretty map, though it can be a little hard to distinguish the coloured rings on each station.
Here’s the key:
The complaints at Principe Pio station, which has an attractive dartboard-like appearance until you remember those colours really mean “slow, subject to breakdowns and with a dodgy entrance”:
Stations with lots complaints on a particular issue seem like they could be due a rethink by the transport authority. Opera station, for example, seems to suffer from slow service, while La Latina received a lot of complaints (407, as of six months ago when the map was compiled) about access to its entrance, which is down a set of steps beside a busy roundabout:
Personally, we’d probably avoid the stations which received complaints about “flooding” first. Busyness we can deal with, but no one wants to be underground when the waters start to rise.
We’ve nothing against Madrid’s metro network (and we’re sure Congosto doesn’t either), but the map is a useful way to visualise potential problem areas. Maps like this could be useful tools for both passengers and transport executives in cities around the world. They could even be integrated into transport apps, which could then tell you if certain stations are particularly busy, or have congested entrances.
Congosto has also made other maps of Madrid’s network, including a map of geolocated tweets on the network and Twitter mentions by station. Go wild.This article is from the CityMetric archive: some formatting and images may not be present.