Category Archives: Data Graphics

Human Visualisation

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One thing I noticed in Vienna, and passing through Brussels airport on the way home, was a number of “augmented reality” advertising displays, ones that detect people in front of them and then show that on their screens. In all the following, Steve Gray of CASA was the subject being visualised.

Here was the first I saw, at Wien Mitte S-Bahn station, where a special “performance” box was taped out on the platform alongside:

Then, at Vienna Aiport, they had a screen above part of a walkway, which augmented various “forest” animals with passersby. Rabbits and deer would appear, grazing on the “grass” when no one was passing. As people approached, the animals would disappear back into the undergrowth. Passing people on the screen left virtual “leaf trails”, while butterflies would occassionally land on their shoulders. Unfortunately my camera didn’t take a great picture, although you can see a butterfly on someone’s hair and some leaf trails here:

On changing through Brussels, a “heat scanner” showed passing people. This was beside a travelator, so your moment of fame was brief:

Vienna itself currently has a aural art installation from the Royal College of Arts. On walking through the Meccano-like sculpture, detectors would sense you and a nearby speaker would start playing a musical sound. Each detector had a different sound type, but they worked in harmony to produce a kind of song, changing as you and other people moved around:

Sadly, on our arrival into Heathrow, we were back to the regular non-augmented ad experience.

Sense and the City

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The Sense and the City exhibition at the Transport Museum in Covent Garden opens today, and runs until March next year. It includes a number of transport visualisations contributed by the team at UCL CASA, including a themed version of my own Bike Share Map, and a similar animation I’ve done for Oyster card tap ins/outs, and also Dr Martin Zaltz Austwick’s bike movement animation. I was along with Martin (pictured above and below!) and some of the others in the team, for the private view on Wednesday.

The exhibition is in three main sections – downstairs there are a number of big screens, showing the aforementioned animations. The area is quite dark, so the graphics have come out really well. The second section is up a spiral staircase (easy to miss) where a number of touch-screen computers show more visualisations from CASA and others, each selectable by the user. The system that runs this will allow us to update the animations during the course of the exhibition, so if we do some newer related work, you may well see it here! Behind this is the last section, which is more conceptual, with a number of “visions of the future from the past” magazine covers, and other bits of futuristic transport technology – a Sinclair C5 and a “Ryno” one-wheeled motorbike. Sadly a Barclays Cycle Hire bike is not there in the flesh, but you don’t have to walk far from Covent Garden to run into them in real life. Finally, just outside the exhibition area is a “smart” bus-stop. You have to look carefully to spot the video camera, which apparently detects how much interest people are taking in the advertising panel, and adjusts its advertising appropriately.

Of course, being the transport museum, all the regular tube trains and buses are still there. The “New Bus for London” mockup is there, as is a classic Routemaster, and it would have been rude not to have gone for a ride…

Below – the Oyster card animation and Steven Gray’s Tweet-o-Meters.

CASA on TV

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Pleased that a feature on spatial data visualisation at UCL CASA has appeared as a video on the BBC News website today. It includes some work I did with Martin Austwick on animating the bike share in London – I did the routing, he did the amazing animation in Processing. It also includes visualisation of bus journeys, Oyster card taps and tweet stats for cities around the world.

A Historical Comparison of OpenStreetMap’s Completeness in Britain

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Dr Muki Haklay,UCL CEGE, has been carrying out some quantitative research into OpenStreetMap’s coverage in the UK, comparing road lengths in each square kilometre, with those in a definitive national dataset, Ordnance Survey Meridian 2. He’s updated his findings every few months, from March 2008 until March this year. Some interesting research findings have been found, such as a potential correlation between an area’s affluence and the map’s completeness, a possible reflection of a contributor demographic. On his suggestion I’ve taken his dataset and overlaid the red/blue under/overcompleteness maps on OpenStreetMap (or Ordnance Survey StreetView) itself, allowing the specific towns and villages that are missing the OSM love, to be identified.

The mashup can be viewed here.

These days, OpenStreetMap’s coverage is pretty good -often exceeding Meridian’s, as service roads, private roads and alleys, that don’t exist on Meridian 2 are added in. There’s still (as of March 2011) some significant holes though, particularly in parts of Wales, the North East and East Anglia.

Note the first four maps only cover England. There is an interesting artefact in the first one – a square around London can clearly be seen, corresponding to the extent of aerial imagery, in that area, that was available via a special agreement with Yahoo for tracing. Outside of that area, only 50-year-old (out of copyright) maps and contributor GPS traces were available. Since May last year, the Ordnance Survey OpenData release, and Microsoft Bing Aerial imagery, which became available at roughly the same time, has significantly accelerated work on the map. I presented on the diverse sources of data at the Society of Cartographers annual conference last year, you can see the slides here.

ITO World’s OS Locator is just one of a number of tools that the OpenStreetMap contributor community in the UK is using to “complete” the map, moving towards the goal of a comprehensive free database of the UK’s (and world’s) streets.

Your Life on a Map – Thanks to the iPhone

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A recent discovery, revealed at the Where 2.0 conference, of a hidden file on iOS4 iPhones and iPads (and on computers that they are synchronised to) is proving to be rather interesting find. The file contains a couple of tables – ‘CellLocation’ and ‘WifiLocation’ that contain records showing times, locations and accuracies of mobile phone masts and wifi points that your phone has come across. [Update: Or more likely, ones that you might expect to come across, based on your current measured location or existing detected masts/wifi.] iPhoneTracker is a great utility which finds the file, parses and displays a gridded heatmap of the places that your iPhone thinks you’ve been to. In my case, it reveals my various trips around London, to towns in England and my travels up to and around the Scottish Highlands in the New Year.

Here’s what a bit of the wifi data on my phone looks like:

You can even see all the MAC addresses of the wifi points (and their locations/accuracies) – again this is nothing you couldn’t collect, and indeed is what Google was busy collecting with their StreetView cars, along with the 360-degree photos. Unfortunately for Google, they also collected the unencrypted data coming from some of these wifi points, which landed them in a bit of bother.

The iPhoneTracker application, as run, grids the data to 1/100th-degree latitude and longitude squares, and only looks at the mobile-phone mast data, rather than the wifi data, as the latter is more likely to be inaccurate (it’s reliant on a look-up database which can go out of date quickly). However, a simple change and recompile of the application in XCode (it’s open source) allows a more accurate map to be included, along with the wifi data if so desired.

The map above shows my travels around London in the last few months, including both the mobile-phone mast and wifi data – the former is generally less accurate and so your location tends to wander, so it shows as circular clumps of small yellow dots. The latter is more concentrated so shows up as the red/purple larger dots, but in fewer locations.

As well as the positional random inaccuracy of the cell-phone triangulations, resulting in these distinctive circles of yellow dots, there is sometimes a systematic inaccuracy. I am 99% sure I haven’t been to East Ham/Barking in the last nine months, but there’s a distinctive clump around there (far right of the screenshot above.)

I’m not going to get into the debate about why Apple has persisted such a file on your phone (and in the computer backup) or whether it’s a good thing that this data is so easily accessible. It’s nothing that’s not on the mobile phone companies’ own databases. The big deal is now you can play with your own location data (and so can someone swiping your computer.) I guess if you don’t have any secrets to hide it’s a great, if imprecise, insight into your spatio-temporal life – tracking how you move around your hometown and indeed the world (my set includes my recent trips to Sicily and Prague).

The background map is from OpenStreetMap. iPhoneTracker is proving so popular, since it was revealed yesterday, that it has quadrupled the normal daily number of map images being served from the OpenStreetMap servers. The gridded visualisation is from OpenHeatMap, written by the same author as iPhoneTracker itself. It’s a great way of showing imprecise, large-volume spatial data like this.

The Geography of Cheap Train Tickets

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Dmitry Adamskiy has built a map of the prices of “advance-purchase” train tickets to anywhere in Great Britain, from several key locations, e.g. London, Birmingham, Liverpool. The dots on the map are colour coded from green to red depending on how cheap or expensive the fares are.

Some striking patterns appear, looking at, for instance the London departure map (shown above). The capital is surrounded by a belt of high ticket prices – the commuter belt – with cheaper tickets generally beyond. The line to King’s Lynn is expensive all the way – but the rest of East Anglia is much cheaper. Birmingham, the south coast and the west coast of Wales are also notable cheap areas. One of the Welsh Valley lines stands out as being much more expensive than the others.

Some other distinctive trends are obvious when departing from Brighton (shown below) – which is only an hour away from London. Suddenly, the eastern half of the country is consistently more expensive to visit than the west. It’s very cheap to get into London on the Southern Railway services, but expensive to visit other parts of the capital, away from the centre. Birmingham and Bristol are quite a bit cheaper cheaper than most of London.

The map can be viewed here. Click on a dot to see the station name and ticket price. There are some notes here.

The background mapping is based on OpenStreetMap. I’m not sure from where Dimitry has obtained his pricing information or station location information from.

Boris Bikes Flow Video – Now with Better Curves!

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Dr Martin Austwick and I have produced an updated version of the animation of Barclays Cycle Hire bikes on a typical weekday:

Martin has once again done some programming magic to show the River Thames, Hyde Park/Kensington Gardens and Regent’s Park to add context, plus the trails for the bike “motes” are longer, allowing the road network to be picked out more easily – and the network lines remain as faint “ghosting” in the video. The bikes are also more blue! Although the bridges aren’t specifically marked, their locations quickly become obvious from the volume of bikes crossing them.

I’ve redone the routing, to fix a few problems around Trafalgar Square and a couple of other obvious places. As before, the routing is done using OpenStreetMap data and the Routino routing scripts, optimised for bike usage (i.e constant speeds on all road types, obeying one-way roads and taking advantage of marked cycleways.) I’ve tweaked the desireability of road types, so that trunk and primary roads are now only slightly less desirable than quieter routes. The traffic in most parts of central London is so slow that, based on my own observations, such roads are not such a significant deterrent to cycling. As before, I’m assuming the bikes go along the “best” route, I don’t know where they actually went. Hires that start and end at the same point – popular in Hyde Park – are shown with the motes spinning around the point.

I’ve also included road curves this time. This means bikes don’t go in straight lines between junctions. This was particularly noticeable when they cut the corner of the Thames in the last animation! Watch the bikes as they carefully curve around the kinks of West Carriage Drive in Hyde Park, around the graceful arcs of Regent Street and Aldwych and along the Victoria Embankment. (I don’t think there are many other classic curves in the central London area?)

Expand the video to full-screen, and, if your connection can take it, click the HD button to get a higher-quality with even bluer bikes!

The data for the bikes themselves is from Transport for London, with the Thames, parks and the underlying network being faithfully drawn by OpenStreetMap contributors. One of the great advantages of using OSM data – apart from it being easy to access, is it’s often very up-to-date. For example, you can see the kink at the northern end of Blackfriars Bridge, on the animation, where the road bends around the Blackfriars Station redevelopment site.

LinkedIn Network Maps

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I’ve just come across the network map generator from LinkedIn Labs, the “cool fun stuff” page where LinkedIn employees put their “20%-time” projects. I don’t use LinkedIn hugely, but have built up enough contacts on the “professional” social network now, from accepting connection requests, for a reasonably interesting map to be produced. You can see mine here. Four clumps are immediately spatially apparent: I identify them as University, Graduate Job, Current Job (CASA) and Orienteering. The software itself identifies and colour-codes six categories – it separates out my graduate job clump into the interns and the people I met once I came back for real – and splits the current job clump into the current and previous role with a closely aligned group (the quantative geographers at UCL.)

The maps are reminiscent of what can be produced in GePhi, an open-source network visualiser that is becoming increasingly popular here in the CASA lab. I produced a similar kind of map a good 15 months ago of my Facebook connections – this latter map has a richer set of connections but people are connected by the simple application of Hooke’s Law (masses on interconnected springs) with straight lines, rather than the sweeping curves of the LinkedIn Lab map, and without the automatic categorisation. You also don’t get yourself placed at the centre, with all the lines leading to you :-) . My connections did however also group roughly into the same categories, showing that once you’ve got your connections, it’s difficult to lose them, no matter what network you are on… ;-)

Flow Animation of Barclays Cycle Hire Bikes

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Dr Martin Austwick and I, here at UCL CASA, have been working on an animation of the Barclays Cycle Hire bikes (aka Boris Bikes) in London, based on the historical flow information that was released by Transport for London (TfL) last month.

Taking one of the busiest days of the scheme – the 4th of October last year, a Monday which coincided with a London Underground strike – Martin has created an animation showing pulsing blobs, or motes, representing the bikes, moving through the 18 hours of the day that the data is available for. As each hire is made, the docking station dot flashes red, and and blue trail starts to leave it, heading towards the destination dock which flashes yellow as it receives a bike.

At the rush-hour peaks (08:45 and 17:45) the map becomes a sea of a 1000 blue pulses, many congregating on a number of key routes in London. The few bridges across River Thames can be picked out as intense bars of light, as commuters travel between Waterloo/South Bank and the City/West End. Hyde Park (middle left) and Regents Park (top left) are noticeable from having few docks in their area, and only a few bikes crossing them. The east seems busier than the west, as the City workers typically commute to work earlier and so dominate the scheme on strike day.

Martin’s used Processing, a rich Java graphics library, to create the animation, which has been then output to video. This allows the up-to-1000 bikes to be animated smoothly and effectively.

The bikes are in official Barclays Blue, although if you don’t view the video in HD, they look slightly washed out. Watch the video on the Vimeo website in HD, although you’ll need a fast computer and a broadband connection.

The routing is done based on the OpenStreetMap data for central London. I used Routino to do the routing, producing a routing file for each of the 137,000 possible journeys between docks in London. The routing is directed, meaning the bikes won’t cycle the wrong way down a one-way street. They also generally avoid trunk roads, such as Euston Road, preferring to use the quieter roads and dedicated cycle lanes nearby. Being able to use the new cycling infrastructure in the routing, is one big advantage of using OpenStreetMap.

A disadvantage is where the routing is wrong. For example, access from the Embankment is not shown correctly. Another problem was the reluctance to cross Trafalgar Square in the centre of the city. This meant I had to move a couple of the docking stations slightly. An example of the latter is shown in the picture here. These quirks, and a few others, result in some bikes flying around the animation extremely fast, as the router sends them a mile up in one direction, around a roundabout, and back down in the other direction. The speeds of the bikes are based on the duration information for the journey, which is included in the data, so they start and finish at the right time.

The routing is the “best guess” route, based on the assumption that the majority of cycle users will know the “best” route to take. Casual and multi-stop use will be less accurately shown. Bikes which are returned to the same docking station they started from, are shown “orbiting” the dock for four times, before returning to it.

The work follows on from a recent animation showing the TfL buses in London, by Anil Bawa-Cavia, also here at the UCL Centre for Advanced Spatial Analysis in London.

London Surnames: An Onomap of London

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I’ve created a website to showcase a number of bespoke typographic maps that James Cheshire (a Ph.D colleague UCL Geography) has created. The website shows the origin of the most common 15 surnames in each MSOA in London – MSOAs are spatial units roughly encompassing 7000 people.

It’s important to emphasise that these are the origins of the surnames, not of the people themselves, i.e. it is a map of names, not ethnicities. The categories are chosen descriptions of the Onomap groupings that appear when matching surnames and forenames and therefore don’t necessarily line up with associated ethnicities or countries. For example, the high numbers of “Welsh” names appearing is likely not due to lots of Welsh people!

Communities which have more homogenous surnames are more likely to be highlighted on a map like that, at the expense of communities with more mixed surnames – another reason why this map cannot tell you about the proportion of people in a particular area – just their names.

The extract below shows a small Jewish “cluster” of names appearing on the border of Harringay, Hackney and Waltham Forest boroughs – the area known as Stamford Hill, which is an area noted for its large Orthodox Jewish community.

The website itself is nothing particularly special, except that it allows easy panning, zooming and scrolling of James’ eye-catching maps. OpenLayers powers the website, and a custom “pixel-coordinate” projection is used. There is a JQuery slider to scroll through the maps, and the user interface elements adopt the “London street sign” look. The data comes from 2001 so doesn’t account for the likely recent significant population movements around the city in the last few years.

More on James’ blog.