Mashing maps for society

MapTube6 September 2011

Mixing and mashing maps on a website might not be the traditional way of doing social science research, but then MapTube is a child of modern web technology. This website allows you to choose and overlay maps of different combinations to display topics in a visual way – for instance if you wish to look at how levels of income are distributed across the UK compared to education levels.

MapTube, a website resource developed as part of the e-Social Science programme (now renamed Digital Social Research), has been a huge success with over 10,000 registered users, as well as receiving 123,418 hits in 2010 alone. And the possible combinations to mix and mash are almost endless. The map service includes atmospheric science, environmental, geological and archaeological maps, to name just a few. People have been comparing maps of where the UK riots took place with things like English population, immigrant population, and index of multiple deprivation.

"Lots of maps are built from data in well-known geographies, such as countries of the world, postcodes, zip codes, census geographies etc. The idea is that MapTube does the hard bit - packaging our geospatial knowledge into a black box that builds the map visualisation out of their data automatically," explains MapTube developer Richard Milton at the Centre for Advanced Spatial Analysis, University College London.

"What we see now is that people are dealing with the data in a much more dynamic way. Whereas before you had two maps on two different layers and you could only compare them by fading the opacity in and out, now you can have direct access to the data, process it yourself and push it back to MapTube as your own visualisation of the two datasets.

"A map of Twitter messages during the recent riots or results from the 2010 General Election are two good examples of data that’s of interest to the general public if presented in the right way."

The interest is certainly out there, judging by the user numbers. Some of the Twitter visualisations during the time of the UK riots had 30,000 hits in a couple of days. A recent BBC Broadband survey generated a similar level of traffic over a shorter period of time, and resulted in the map-rendering server taking over one million hits in a couple of hours.

Web-based mapping makes it possible to publish geospatial data in a form accessible to the general public, but the web also provides the opportunity to generate new data through crowd sourcing. By using an online form asking a simple multiple-choice question like, "What single factor is affecting you most about the credit crunch?” and getting the user to pick an option and enter his postcode, we can build a map dynamically from this data and watch it change over time. This formed the basis of the SurveyMapper site, which allows the public to run their own online geographic surveys.

However, using 'crowd-sourced data' brings new challenges for researchers when it comes to quality control, Milton cautions.

"For example, somebody has a survey running on SurveyMapper that asks something like ‘How many shops have closed on your high street?’. If you talk to the companies who conduct surveys, their criticism of this approach is that there is no profiling of the people responding to the surveys, and you don’t know how accurate their answers are. All in all I think the crowd-sourced approach should be seen as an additional tool in the social scientist’s toolbox, but one which has yet to mature into a fully developed methodology."

The age of mixing and mashing may just be beginning, with the potential for various uses matching the huge interest. With the current moves towards Open Data, more information is now in the public domain than at any time in the past. With MapTube, we are starting to look at these new sources of data and build tools that can automatically generate maps from tables and data on web pages, reports in PDF format, or Internet datastores.

"We have a different approach to handling the data - which means we are better placed to handle real-time data and constantly changing or transient datasets," adds Richard Milton.

"I do think it opens the door to scales of magnitude that social scientists previously couldn’t access easily, and generates potential new data and issues that they haven’t had to address before."