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Case study:
Data City: Integration and visualisation of spatial and socio-economic data in an urban context

Comparing data sets

The combination of data sets allows the correlation between each of the individual data sets. The difference between a standard statistical correlation and the one illustrated below is that the latter visually illustrates the relation between the two variables relative to their location in space.

The multiple data sets are a combination of two data sets, using transparency and different colours to represent the two sets of volumes.

Combined data sets 1

The expected relation between these two data sets is that owners of HMO's will seek inexpensive housing to try to maximise their earnings and that they will spend as little as possible in repairs, as outgoings affect profits.

One can see a general increase in property prices (red) as one gets closer to the High Street (Byres Road). At the same time one detects a decrease in the amount of HMO's (blue) when moving in the same direction.

Combined data sets 2

The data on house prices based on sales (red) in the last 5 years do not cover all the properties in the study area. However, as Council Tax assessments (light blue) were done many years ago and have not been updated, one would expect that current sale prices should be significantly higher.

The comparison between these two data sets confirms this view.

Combined data sets 3

We previously noted that the higher densities of HMO's (blue) were concentrated in the middle of an East/West vector. On the other hand we noted that repair costs (purple) were relatively homogeneously distributed.

The two data sets do not appear to be strongly correlated, a finding which would go counter to the commonly held belief that one should find the concentration of buildings in need of repair in the same areas as HMO's.

Combined data sets 4

One would expect to find that the older properties (yellow) would demand more care and thus present its owners with the largest repair bills (purple). However this is distorted when an extensive programme of rehabilitation is undertaken. This is the case in the East part of the study area. However, we did find that there was a slight concentration of large repair costs in the South East corner of the study area which does contain some of the oldest buildings.

Last updated: June 24, 2003