Led by Dr Martin Zaltz Austwick and Dr Duncan Smith, this module introduces students to methods of visualisation and data mining within the geospatial domain. Developed as a group project, the module aims to provide an understanding of the juxtaposition between research, data capture and data display methodologies. It is designed to build upon the taught sections of the course to develop initial research questions for the dissertation.
Themed around Local Connections, the students linked in with the exhibitions and activities happening at the London Transport Museum‘s Designology season to create their own visions of bus stops which incorporate Smart City data feeds to engage the captive audience of bored people waiting for a bus.
Our first group (Anouchka Lettre, Luigi Rossi and Thomas Russell) based their design on the swiss railway clock and the “multiple time zone” views seen in 20th Century banks and international businesses.
This was in line with a design philosophy which used different scales of time to show users the now (which buses are on their way), the near (where can I get a coffee/meal/stroll within a few minutes), and the more distant future (what events will happen close to this location in the coming hours and days). You can see an example of this for Goodge Street (CASA’s closest tube station at time of writing), but the team have worked up an API which takes data from Eventbrite, Google Places, Wikipedia, and elsewhere – meaning this will work for any bus stop in London.
The team ascertained that people buying coffee or a meal want quality, value and convenience – the radar plot in the bottom left corner represents the users preferences (blue) along with the properties of the cafe (orange) so they can see at a glance how close is comes to their criteria.
They experimented with dynamic basemaps, with different coloration and even 3D rendering of shadows to represent the passage of time, and Ben Day-style print effects to match the appearance of the group’s data visualisations to print media onsite:
Our second group definitely has the best project title we’ve ever seen at CASA, and they set themselves the challenging task of working within the existing design framework of TFL’s bus stops, designing elements for each part of the stop:
The team had certainly set themselves a design challenge to work with such a visually rich template and integrate real-time data feeds in a legible way. Their solution focussed on only drawing attention to key elements, and giving users a moving indicator of where their bus is. Here is a excerpt:
Notice how they have de-emphasized irrelevant routes, represented buses with colour-coded circles to prevent clutter when they overlap, and retained detailed summary information about all the local buses on the right hand side. They brought this animated spider map together with local information to provide this dashboard view of where you are now:
The group also provided an animated 3D view of the local space, building on the bus arrival information and models of the buildings in the local environment.
Heidi, Kaisa, Yuefeng (“Jeff”) and Aditya wanted to understand the marathon from a data-driven perspective – both as an athletic event, and as one which has impact across the world. They set about gathering data from the Marathon site about runners, and in parallel, mining Twitter for buzz running up to the event by searching on marathon-related hashtags across the world. The also gathered data on race day in London in order to see live tweets as they happened over the course of the race.
These were the datasets, and from this the team was able to generate a diverse but coherent set of visualisations: maps of tweets around the world, visualisations of international runners travelling to the UK, and visualisations of the race itself drawn from real running data. The 2D version of this incorporates weather and curated tweets of encouragement; the 3D version has a detailed 3D model of London and a high-resolution basemap.
The group then synthesised these elements into the coherent and concise video you see above. Choosing a consistent colour palette and base map glue the individual pieces together; the use of a voice over draws to viewer in and ties the elements together further.
In the course of this project, the students used elements from all aspects of their visualisation course – 3D environments, data collection, and programmatic visualisation – but it’s what the elements have in common that makes for an effective project.
Activity Beyond Barriers, 2013-14
Students mined data from Oyster Cards (London’s smart card for transportation), identifying patterns of travel for users with mobility barriers. The group created a series of GIS analyses and visualisations, including these powerful 3D visualisations showing real data across the city in the course of a typical day, with users with mobility barriers highlighted in red.
Active Thames, 2014The group focussed on the River Thames (which runs through the centre of London), and its role as a driver of economic and cultural activity in our capital. This visualisation drew together data from Twitter, Instagram, River Buses and real building models, to create a flythrough of the Thames’ active presence.
UCLive Augmented Reality Campus, 2012-13
Students created an augmented reality app for Android Tablets which triggers from the UCL map (found across the campus) – showing twitter activity, the availability of computers, geolocated samples from the “Sounds of UCL” Soundcloud stream, and modelling transport patterns and availability. Members of the team went on to develop a similar app for English Heritage in a project that summer.
Infinite Museum, 2011-12
The procedurally-generated museum that you see in this flythrough contains a showcase of visualisations from throughout the students’ study – from urban models to cellular automata. They created an interactive that generated the rooms of the museum on the fly based on user preference.