Presentation given by Chris Gale on Friday 13th April at GISRUK 2012. For more information on GISRUK 2012: www.lancs.ac.uk/gisruk2012 For further research by Chris Gale: mapblog.in

1. UCL DEPARTMENT OF GEOGRAPHY
Open Geodemographics: Open Tools
and the 2011 OAC
Chris Gale* Muhammad Adnan Paul Longley
mapblog.in gis-tech.co.uk paul-longley.com
@geogale @gisandtech
* Conference attendance kindly supported by RGS-IBG funded QMRG bursary
UCL Department of Geography, Gower Street, London, WC1E 6BT

2. UCL DEPARTMENT OF GEOGRAPHY
Outline
• What is Geodemographics?
• Need for Open Geodemographics
• GeodemCreator
• The 2011 Output Area Classification
• Summary

3. UCL DEPARTMENT OF GEOGRAPHY
Geodemographics
• The analysis of people by where they live
• Areas can be described by the characteristics and
attitudes of those people who live in them
• Based on the concept that similar people with similar
characteristics are more likely to live within the same
locality and that such area types will be distributed in
different locations across a geographical space
• Commercial (MOSAIC, ACORN) and free (OAC)
classifications available

4. UCL DEPARTMENT OF GEOGRAPHY
Commercial Geodemographic
Classifications
• Created as ‘black box’ systems
(Longley and Singleton, 2009)
• Closed methods are used with little documentation
• Little information is given regarding the data
inputs, normalisation and weighting procedures, and
clustering methods employed

5. UCL DEPARTMENT OF GEOGRAPHY
Need of Open, Transparent, and Flexible
Classifications
• Increased amount of data sources due to ‘open data’
initiatives
– ONS NeSS data exchange, London data store, Crime data API
• Need of open methods
– Open method of Estimation, Normalisation, and Clustering
procedures
• Open public consultation

6. UCL DEPARTMENT OF GEOGRAPHY
Need of Open, Transparent, and Flexible
Classifications
• A number of statistical packages could be used for
building geodemographic classifications
– R, SPSS, Microsoft Excel
• No unified software utility exists that could be used for
building open, transparent, and flexible classifications
• ‘GeodemCreator’ is a unified software utility for
building geodemographic classifications

7. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator
• A cross platform java software utility for building
geodemographic classifications
• Requires ‘Java’ and ‘R’ installed on user’s machine
• Geodemographic classifications could be created for
any geographical level and by using any data set
• Users can combine census data with their own data
sources

8. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator
• Operates in ‘Basic’ and ‘Advanced’ modes
– Basic Mode is for inexperienced and new users
– Advanced modes is for experienced users
• Clusters the data by using k-means clustering
algorithm

9. UCL DEPARTMENT OF GEOGRAPHY

10. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study
• A Socio-economic and Ethnic classification of Greater
London
• Created by using 41 OAC variables and 12 ethnicity
variables (created from ethnicity data source
http://worldnames.publicprofiler.org)
• GeodemCreator was used for building the final
classification

11. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study Data Sources
• Variables V1 to V41 from the 2001 OAC
• Variables V42 to V53 ethnicity
V42: ‘European’ ethnic group
V43: ‘East Asian & Pacific’ ethnic group
V44: ‘Muslim’ ethnic group
V45: ‘Greek’ ethnic group
V46: ‘English’ ethnic group
V47: ‘Nordic’ ethnic group
V48: ‘African’ ethnic group
V49: ‘Japanese’ ethnic group
V50: ‘Hispanic’ ethnic group
V51: ‘Celtic’ ethnic group
V52: ‘Jewish’ ethnic group
V53: ‘South Asian’ ethnic group

12. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study Results
• A Socio-economic and Ethnic classification of Greater
London:

13. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study Results
• GeodemCreator also produces radial charts for each
cluster solution
English and European ethnic groups Well off and educated Asian families
living in suburban areas

14. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study Results
English, European, and Celtic fringe Poor Asian Families
city commuters

15. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study Results
Childless European city dwellers Native blue collar communities

16. UCL DEPARTMENT OF GEOGRAPHY
GeodemCreator Case Study Results
English and European ethnic groups
living in council properties

17. UCL DEPARTMENT OF GEOGRAPHY
The 2001 Output Area Classification (OAC)
• Groups the UK population
into:
– 7 Supergroups
– 21 Groups
– 52 Subgroups
• Only data source used is the
2001 Census
– 41 Variables
• Variety of organisations use it
including local government
and commercial companies

18. UCL DEPARTMENT OF GEOGRAPHY
The 2011 Output Area Classification
• Building on the success of the 2001 OAC
• The 2001 OAC’s real achievement was showing that
open-source geodemographic classifications were
possible
• Can utilise developments in computing over the past 6
years, since the 2001 OAC’s publication, to make
improvements
• Can be produced using open-source software (if
required) with a fully open and transparent
methodology

19. UCL DEPARTMENT OF GEOGRAPHY
The 2011 Output Area Classification
• Not just a repeat of the 2001 Output Area
Classification
• Methodology that will possibly not rely on 100%
Census data
• Enhanced outputs to cater for different potential users
• Designed to allow easy creation of bespoke variants
– Variables and/or Geography
– Automated variable selection depending on user criteria
• e.g. variables used for a national classification not necessarily being
suitable for a regional classification

20. UCL DEPARTMENT OF GEOGRAPHY
2011 OAC Variables
• Code used to auto-select best variables for desired
purpose
• Allows for a fully transparent and repeatable
methodology
– Variable selection the only “black box” element of the 2001
OAC
• Allows for wider scale bespoke geodemographics
– A user with no geodemographics experience can produce
their own classification by selecting the
variables, standardisation method, number of clusters.
– Removes any technical barriers that could prevent wider
adoption of bespoke geodemographic classifications.

21. UCL DEPARTMENT OF GEOGRAPHY
Bespoke Geodemographic Classifications
• Categorised into 3 main types:
– Using the same data already provided in classification.
– Changing the number of variables used to create a
classification.
– Uploading other data that was not originally included into a
pre-existing classification or creating a new classification
from scratch.
• In the case of OAC this could resolve a problem when
used at a regional level
– London is an example of one such region that OAC does not
classify very well.

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23. UCL DEPARTMENT OF GEOGRAPHY
The Hull City Council Classification
• Bespoke free area
classification of
Hull
• 45 Census
Variables used
• 10 Groups in 3
hierarchies

24. UCL DEPARTMENT OF GEOGRAPHY
2011 OAC and Open Data
• Would it be better to use potentially “newer” Open
Data (when compared with the 2011 Census)?
• How much of a problem is the lack of data currently
available at OA level?
• Using Open Data raises a lot of questions:
– What sources of Open Data should be used?
– What should the coverage of the Open Data be?
– Does the integrity of the Open Data matter?
– How often should the Open Data sources be updated?
• Beyond 2011

25. UCL DEPARTMENT OF GEOGRAPHY
On-The-Fly Clustering
• To meet the changing and varying needs of users a
dynamic classification environment needs to be
created
• Ability to create bespoke classifications a requirement
– both for different geographies (e.g. London or UK) and the
range and number of variables utilised (e.g. Census and/or
non-Census) with an additional weighting capacity
• Will require clustering to happen in real-time
• Research of users specific has been undertaken
– 2011 OAC User Engagement (run in partnership with the
ONS)
– Results to be published by ONS by late April

26. UCL DEPARTMENT OF GEOGRAPHY
On-The-Fly Clustering Objectives
• Find optimum real-time clustering solution
– Using mean Within-Cluster Sum of Squares (WCSS) value to
determine optimum cluster solution using K-Means.
– Number of cluster algorithm iterations to use to create a good
clustering solution that does not result in poor functionality.
• Create repeatability
– Overcome inherent random seeding of K-Means that results
in an OA remaining in the same cluster group but being given
a random cluster assignment (e.g. a number from 1 to 7) for
every iteration.
• Incorporate different data sources
– Both Census and non-Census data

27. UCL DEPARTMENT OF GEOGRAPHY
What the Within-Cluster Sum of Squares
Value means
• Lower the mean value the more homogenous (i.e.
better) the final cluster groupings are
– Clustering using the lowest WCSS value can therefore be
considered to create the optimum cluster groupings.
• Using anything other than optimum cluster solution can
have differing results depending on the dataset and
level of geography

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32. UCL DEPARTMENT OF GEOGRAPHY
Summary
• The 2001 OAC was an important first step for open
source geodemographics
• The 2011 OAC can build on the successes of the 2001
OAC
• Tools like GeodemCreator can be used to create
bespoke geodemographic classifications easily and
without any “expert” knowledge
• The 2011 OAC is still in the planning phase but should
be released in some form by late 2012/early 2013

33. UCL DEPARTMENT OF GEOGRAPHY
Any
Questions?