Mapping the data city: London's cartographers past and future

London Essays – Issue 2: Technology

Mapping the data city: London's cartographers past and future

If you want to get to know London the first thing you may reach for is a Tube map. You will soon realise, however, that Harry Beck’s series of interconnecting lines are pretty useless as a street-level navigation tool – they only come into their own underground.

By Dr James Cheshire

Beck’s genius was to appreciate that in the darkness and bustle of an Underground tunnel the most important thing is how the lines connect, not the geographical positions of the stations. Thanks to Beck, the trip from Oxford Circus to South Kensington can be boiled down to “light blue to Victoria then green/yellow to South Kensington”. Maps are the product of a series of editorial decisions taken by the mapmaker – and the more intelligent these decisions are, the more effective the map will be.

With all the hyperbole about ‘Big Data’ it is easy to forget that the art of map making lies in extracting the key information and presenting it in a way that is easy to read. In Beck’s case this was how the stations and lines connect to each other. In the fight against diseases proliferating in 1850s London, however, it was John Snow who understood that the key information could be shown through mapping the incidence of cholera along Soho’s streets, so identifying a water pump as the source of a deadly outbreak.


Snow knocked on doors and asked questions to gather his data – what would he make of the technological advances transforming the way we study cities in the 21st Century? Data are now collected by servers “in the cloud” and analysed in offices and control rooms. There is no doubt that such developments have had a hugely positive impact on city life and it is perhaps fitting that, as the home of a number of urban data pioneers, London has been leading the way in generating and releasing data. Each time a Londoner sends a Tweet or rides a Boris Bike, they are contributing data that can be analysed and, through the creation of the London Datastore, the GLA has made much of this information freely available to anyone who cares to have it. Transport for London also makes much of its data accessible to the public, releasing a monthly “Performance Data Almanac”, in addition to diligently answering hundreds of Freedom of Information requests. All this is without even considering the trove of data resulting from the UK’s hugely detailed census. Few capital cities could map the relationship status of their inhabitants, for example, in such detail.


Open data enable us to do the fundamentals better – we can ask questions about child poverty and educational attainment, causes of death and the time spent by our emergency services dealing with false alarms. We can follow the police helicopters’ flights on Twitter but we can also request more specific details about their daily activities. We can have fun charting the city’s most photogenic features or find out how many Lobetoothed Piranhas there are in London Zoo (15 according to the zoo’s 2014 census).


London’s data landscape is therefore a tremendously varied and exciting one, but for us to reap its full benefits there is still work to do. Many more datasets could be opened up to the public, while more could be done to make it easier to find and use already accessible ones. Perhaps most importantly, we also need to ensure that the raw data we have can be turned into meaningful information to improve the city. Here the challenge is a little greater, since manipulating large databases or sending requests via APIs requires skills few Londoners possess. In this sense, increasing data provision is by no means the same as increasing data access. The good news is that a growing number of datasets are being made more user friendly, with the likes of “dashboards” offering accessible snapshots of key trends in the data behind them and interactive maps that can show patterns without the need for number crunching.

Those of us who work in London’s universities are acutely aware that we need to enthuse our students about the power of data and teach them the technical skills to make full use of it. At UCL, for example, we are part of an initiative known as “Q-Step” that will be teaching undergraduates in Geography, Epidemiology and Political Science just the kinds of skills they need to wrangle large urban datasets. There are further initiatives too at the postgraduate level, with courses focused on “Smart Cities” and “Big Data” all capitalising on London’s increasingly complex and open data infrastructures. The aim is to send graduates from a broad range of backgrounds into the workplace with the skills and enthusiasm to make a difference using the billions of data points at their fingertips. Maps offer just one of the ways our students can do this. I like to think some could have the same impact as Harry Beck or John Snow.