Mark Thurstain-Goodwin enjoys seeing Ipsos MORI put spatial data in front of local authorities
It’s nice to have your career choice reaffirmed from time to time. I did feel a bit of that special warm glow this month at a great event organised by our clients Ipsos MORI to launch their National Indicators Mapping Application (NIMA), developed by Geofutures.
What set me glowing? Being reminded that a picture is worth a thousand words (the bumper-sticker of GIS professionals everywhere). In fact it was two pictures, so maybe that’s two thousand words. Here they are:
Twin images of perception data in North London from Ipsos MORI's NIMA app show strong correlation
The audience, a who’s who of local authority research heads and their suppliers, got a whistle-stop tour of all Ipsos MORI’s work in this important market, and NIMA was centre stage. All authorities now have to poll their electors on 198 National Indicators of satisfaction and the factors affecting it, and NIMA provides instant online insight into the results. Side-by-side ‘double view’ comparisons of maps like these are a key part of the application.
What these two visualisations show are three key reasons why mapping these kinds of data is such a compellingly good idea: the correlation of the two hotspots, the fact that both are visible despite the ward boundaries, and the geographical context that the map offers.
So firstly, the two maps describe responses to two different survey questions: overall satisfaction/dissatisfaction with the area as a place to live on the left, and perception of social cohesion on the right. Only by locating these respondents on the map in a statistically smoothed data landscape can we so immediately see the close spatial correlation of the low-perception hotspots. For a local authority looking for ways to focus resources in hotspots of this kind, to deal with specific issues where they are being experienced and to maximise policy effectiveness, the benefits are obvious.
And if your local authority is only offering National Indicator results by ward, IMHO you want to be asking how efficiently they are spending your council tax. If the same results had been aggregated by ward, the hotspots would disappear altogether. It certainly wouldn’t be evident that dissatisfaction and issues of social cohesion were concentrated in one area which impacts sections of four separate wards. Tying data to actual location, rather than some arbitrary zonal boundary, is a key benefit of GIS analysis. Cue warm glow.
And a map does another simple but fundamental thing: it shows what’s on the ground in the hotspot locations. These two hotspots have a major roads running through them. Does this mean we’re looking at a pocket of high-density roadside dwellings choked with exhaust fumes, whose residents are struggling with low incomes, transient neighbours and the social issues that go with them? The sort of neighbourhood where local authorities really need to send their outreach workers?
Intriguingly, no. Zoom into an aerial image of Hendon Wood Lane and you’ll find leafy open spaces, substantial detached houses, gardens and even a smattering of swimming pools. This is where the hotspots of community dissatisfaction and perception of poor social cohesion are undoubtedly to be found, but not I suspect because of social deprivation.
Again, a map visualisation proves its worth, hinting at a fascinating little area for further exploration.
Tags: clients, data, GIS, mapping
