Category: Data Graphics

As a weekend project, I’ve made an interactive version of my London North/South artwork.

As well as the blue and red house silhouettes, assembled in QGIS, I’ve added in GeoJSON files of the River Thames (from Ordnance Survey Vector Map District, like the buildings) and of tube/DLR/Overground stations – the location/name/network data is from this GitHub file and I’ve applied a custom styling in OpenLayers 2, with station name styling inspired by the NYC Subway signs. The positional information comes from an OpenLayers control – I’m using a utility function to modify the output to use degrees, minutes and seconds. Finally, the naming popup is a set of UTFGrid JSON files (with 2-pixel resolution) based on OpenStreetMap data for polygons. Where the polygon has a building, leisure or waterway tag, I’m extracting a name, if available, and showing it. The coverage here is therefore only as good as building naming is in OpenStreetMap. I could potentially add in street names in the future.

Try it out here.

Cross-posted from Mapping London, edited slightly.

This is a map of geolocated Tweets for the whole world – I’ve zoomed into London here. The map was created by Eric Fischer of Mapbox, who collected the tweets over several years. The place where each tweet is posted from is shown by a green dot. There are millions and millions of tweets on the global map – in fact, over 6.3 billion. The map is zoomable and the volume of tweets means that popular locations stand out even at a high zoom level. The dots are in fact vectors, so retain their clarity when you zoom right in. The map is interactive – pan around to explore it.

If you think this looks familiar, you’d be right. Mapping London has featured this kind of social media ‘dot-density mapping’ a few times before, including with Foursquare and Flickr (also Eric’s work), as well as colouring by language. The key difference with this latest map is the sheer volume of data. By collecting data on geolocated tweets over the course of several years, globally, Eric has assembled the most comprehensive map yet. He has also taken time to ensure the map looks good at multiple zoom levels, by varying the dot size and dot density. He’s also eliminated multiple tweets that happen at the exact same location, and reduced some of the artefacts and data quality issues (e.g. straight lines of constant latitude or longitude) to produce perhaps the cleanest Twitter dot-density map yet. Zooming out makes the map appear somewhat similar to the classic night-time satellite photos of the world, with the cities glowing brightly – here, London, Paris and Madrid are prominent:

However it should still be borne in mind that while maps of tweets bear some relationship to a regular population density map at small scales, at large scales they will show a bias towards places where Twitter users (who may be more likely to be affluent and younger than the general population) live, work and socialise. The popularity of the social network also varies considerably on a country-by-country basis. Some countries will block Twitter usage altogether. And in other countries, the use of geolocated tweets is much less popular, either due to popularity of applications that do not record location by default or a greater cultural awareness of privacy issues relating to revealing your location when you tweet.

Above: Twitter activity in central Edinburgh, proving once and for all that the East End is a cooler place than the West End.

From the Mapbox blog. Found via Twitter, appropriately. Some of the background data is © OpenStreetMap contributors, and the map design and technology is © Mapbox.

If you are a Londoner but felt that Tube Tongues passed you by, maybe because you live in south-east London or another part of the city that doesn’t have a tube station nearby, then here’s a special version of Tube Tongues for you. Like the original, it maps the most popularly spoken language after English (based on 2011 Census aggregate tables released by the ONS, via NOMIS) but instead of examining the population living near each tube station, it looks at the population of each ward in London. There are 630* of these, with a typical population of around 10000. I’ve mapped the language as a circle lying in the geographic centroid of each ward. This is a similar technique to what I used for my local election “Political Colour” maps of London.

A few new languages appear, as the “second language” (after English) in particular wards: Swedish, Albanian and Hebrew. Other languages, which were previously represented by a single tube station, become more prominent – Korean around New Malden, German-speaking people around Richmond, Nepalese speakers in Woolwich, Yiddish in the wards near Stamford Hill and Yoruba in Thamesmead. Looking at the lists of all languages spoken by >1% of people in each ward, Swahili makes it on to a list for the first time – in Loxford ward (and some others) in east London. You can see the lists as a popup, by clicking on a ward circle. As before, the area of the circles corresponds to the percentage of people speaking a language in a particular ward. The very small circles in outer south-east London don’t indicate a lack of people – rather that virtually everyone there speaks English as their primary language.

English remains the most popularly spoken language in every ward, right across London. Indeed, there are only a three wards, all in north-west London, where it doesn’t have an absolute majority (50%). London may seem very multilingual, based on a map like this, but actually it is very much still Europe’s English-speaking capital. See the graphic below, which shows the equivalent sizes the circles are for English speakers, or click the “Show/hide English” button, on the interactive map.

Here’s the interactive map. There’s also a ward version of Working Lines.

* I’ve ignored the tiny City of London ones except for Cripplegate, which contains the Barbican Estate.

Background map uses data which is copyright OpenStreetMap contributors. Language data from the ONS (2011 Census).

I’ve extended my map of tube journeys and busy stations (previous article here) to add in an interesting metric from the 2011 census – that of the second most commonly spoken language (after English) that people who live nearby speak. To do this I’ve analysed all “output areas” which wholly or partly lie within 200m radius of the tube station centroid, and looked at the census aggregate data for the metric – which was a new one, added for the most recent census.

See the new map here.
Also available as an A2 print.

Each tube station has a circle coloured by, after English, the language most spoken by locals. The area of the circle is proportional to the percentage that speak this language – so a circle where 10% of local people primarily speak French will be larger (and a different colour) than a circle where 5% of people primarily speak Spanish.

Language correlates well with some ethnicities (e.g. South Asian) but not others (e.g. African), in London. So some familiar patterns appear – e.g. a popular, and uniform, second language appearing at almost all Tower Hamlets stations. Remember, the map is showing language, not origin – so many of the “Portuguese” speakers, for instance, may be of Brazilian origin.

Click on each station name to see the other languages spoken locally – where at least 1% of local speakers registered them in the census. There is a minimum of 10 people to minimise small number “noise” for tube stations in commercial/industrial areas. In some very mono-linguistic areas of London (typically in Zone 6 and beyond the GLA limits) this means there are no significant second languages, so I’ve included just the second one and no more, even where it is below 1% and/or 10 people.

This measure reveals the most linguistically diverse tube station to be Turnpike Lane on the Piccadilly Line in north-east London, which has 16 languages spoken by more than 1% of the population there, closely followed by Pudding Mill Lane with 15 (though this area has a low population so the confidence is lower). By contrast, almost 98% of people living near Theydon Bois, on the Central Line, speak English as their primary language. English is the most commonly spoken language at every tube station, although at five stations – Southall, Alperton, Wembley Central, Upton Park and East Ham – the proportion is below 50%.

A revealing map, and I will be looking at some other census aggregate tables to see if others lend themselves well to being visualised in this way.

I’ve also included DLR, Overground, Tramlink, Cable Car and the forthcoming Crossrail stations on the map. Crossrail may not be coming until 2018 but it’s very much making its mark on London, with various large station excavations around the capital.

The idea/methodology is similar to that used by Dr Cheshire for Lives on the Line. The metric was first highlighted by an interesting map, Second Languages, created by Neal Hudson. The map Twitter Tongues also gave me the idea of colour coding dots by language.

One quirk is that speakers of Chinese languages regularly appear on the map at many stations, but show as “Chinese ao” (all other) rather than Cantonese, whereas actually in practice, the Chinese community do mainly speak Cantonese (Yue) in London. This is likely a quirk of the way the question was asked and/or the aggregate data compiled. Chinese ao appears as a small percentage right across London, perhaps due to the traditional desire for Chinese restaurant owners to disperse well to serve the whole capital? [Update – See the comments below for an alternative viewpoint.]

The TfL lines (underground, DLR etc), station locations and names all come from OpenStreetMap data. I’ve put the collated, tidyed and simplified data, that appears on the map, as GeoJSON files on GitHub – see tfl_lines.json and tfl_stations.json. The files are CC-By-NC, licensing information is here.

Above is a Wordle of the messages displayed on the big dot-matrix displays (aka variable message signs) that sit beside major roads in London, over the last couple of months. The larger the word, the more often it is shown on the screens.

The data comes from Transport for London via their Open Data Users platform, through CityDashboard‘s API. We now store some of the data behind CityDashboard, for London and some other cities, for future analysis into key words and numbers for urban informatics.

Below, as another Wordle, are the top words used in tweets from certain London-centric Twitter accounts – those from London-focused newspapers and media organisations, tourism organisations and key London commentators. Common English words (e.g. to, and) are removed. I’ve also removed “London”, “RT” and “amp”.

Some common words include: police, tickets, City, crash, Boris, Thames, Park, Festival, Bridge, bus, Kids.

Finally, here’s the notes that OpenStreetMap editors use when they commit changes to the open, user-created map of the world, for the London area:

Transport and buildings remain a major focus of the voluntary work on completing and maintaining London’s map, that contributors are carrying out.

There is no significance to the colours used in the graphics above. Wordle is a quick-and-dirty way to visualise data like this, we are looking at more sophisticated, and “fairer” methods, as part of ongoing research.

This work is preparatory work for the Big Data and Urban Informatics workshop in Chicago later this summer.

Thanks to Steve and the Big Data Toolkit, which was used in the collection of the Twitter data for CityDashboard.