The Census of Population: 2000 and Beyond

Manchester 22-23 June 2000

“Small Area Statistics On-line”

Dr Erik Thomasson, GIS Manager, City of Bradford MDC

1.0 Abstract

This paper describes a methodology developed in Bradford to make Census (and other geographically referenced datasets) available to users ‘on-line’ using Internet browser technology. It provides a means of both sharing progress and of disseminating details of the development work and outcomes to date in the interests of encouraging scrutiny and seeking constructive contributions from interested parties. A basic working knowledge of the Census and issues around the derivation and analysis of small area statistics is assumed.

The paper does not dwell on the procedure by which Bradford’s small area population estimates themselves have been derived. Details of this are available elsewhere ⁷. Instead, it concentrates on describing how in Bradford, a mechanism has been developed which, we believe, overcomes one of the major traditional constraints of small area statistics – that of prescriptive geographical boundaries, (Wards and Enumeration Districts). The pilot project has put into practice a technique which delivers ‘boundary-free’ data which the user can select via a map-based interface either using any of a range of existing boundaries, or, most significantly, by drawing their own custom area. Initial development work used desktop GIS (Geographical Information System) software (ESRI’s ArcView). A ‘Web’ prototype using (Autodesk’s Mapguide software) has since been developed working on the Council’s internal Intranet. The application is shortly to be made available on the World Wide Web (extending the Mapguide application), in so doing, revolutionising access to demographic data and other small area statistics.

The project has achieved four key outcomes:

· Boundary-free Census data

· Combination of the Census with other geographically referenced data

· Ease of use via an intuitive user interface

· Improved dissemination and a broadening of the use of geo-referenced data.

2.0 Introduction

2.1 Background

My position is that of GIS Manager for City of Bradford MDC, and in that capacity I coordinate the implementation and development of Geographical Information Systems across the Council. In my previous job I was responsible for the delivery of Census information (via SASPAC) to Leeds City Council Department of Social Services. Because the Census data is collected and made available via a geographic base, it lends itself directly to incorporation into GIS. My present post is located within the Policy & Research Unit of the Council, a corporate unit also responsible for the dissemination of

population data. Because of this, I work closely with colleagues working with the Census and with population forecasting. This relationship has helped Bradford to develop an integrated approach to the provision of population data through a GIS-enabled interface, and latterly, through a GIS web browser with a view to universal ‘on-line’ access to the data over the World Wide Web.

2.2 The Philosophy behind Bradford’s work

Reliable population figures are required by the Council in order to plan and target resources and services appropriately. The Unit has historically recognised the need for inter-censal updates in the population figures provided to customers and has had in place since 1998, a system for calculating small area population estimates to replace the increasingly out of date 1991 Census. It was therefore considered desirable to be able to disseminate these estimates as widely as possible. Facilitating ease of access to updated population figures through the removal of barriers to access was seen as a key objective of the project.

In recent years, the growing prominence of statistics in the performance monitoring of Local Government has increased demand from strategic planners – not least since performance monitoring requires reliable population data as a denominator. Joint planning and Joined-up working have become part of the Modern Local Government vocabulary since the 1998 White Paper ⁸. Cabinet Office is also keen to develop geographic referencing to provide ‘Better Information’ ⁴. The Unit recognised that joint access to data would be a prerequisite of this model of working.

There has also been a growth in the demand for demographic data to support a range of regeneration bids, in particular, successive rounds of the Single Regeneration Budget bidding process. Similarly, there has been a growth in demand from Community groups seeking access to ‘official’ statistics to support their bids for lottery funding and other grants. We wanted not only to be able to serve such bids, but also to play a more active role through the provision of a tool which might assist in the drawing up of the Bid area boundaries themselves. The penetration of IT generally and the increasing sophistication of the general public and the proliferation of IT and statistics modules in schools and in college courses has also fed demand for data. This project therefore aims to address access to data for use in either an operational or strategic management context, internally within the Council and externally by other agencies, community groups and individuals.

The initiative has been fuelled by a desire to improve the service offered by the section, but also to reduce the burden on staff in the Unit caused by the burgeoning demand for our services due to the above developments (in particular time consuming one-off bespoke requests for data). The aim therefore of our ongoing work is to streamline the process of deriving population counts for any geographical area, into an intuitive non-technical exercise which potential customers can access and undertake themselves.

3.0 The ‘Deliverables’

3.1 Population and Census data

The prototype site currently utilises small area population estimates produced collaboratively by the Council and Bradford Health Authority. The estimates incorporate patient records from the Family Health Service, the 1991 Census, the Electoral Register and District population estimates produced by the Council. In addition, an ethnic breakdown has been achieved with the aid of Bradford’s Asian Names Program (‘Nam Perchan’). Though not as comprehensive as ideally desired, this has enabled a split into South Asian Origin and All other groups. Ward level estimates were published in July 1997, while ED level estimates were completed in March 2000. More detail of this methodology is available from the Unit ⁷.

The site will also include a cross-section of other small area counts for variables covered in the 1991 Census for which no contemporary alternative is available. In due course all data will be reviewed once data from the 2001 Census is published.

3.2 Other Council data

As well as delivering demographic data derived from the Census, it was decided that population data should be combined with other data sources. For example, data for Council services such as Education and Social Services might be combined with population data to calculate rates of service delivery per 1000 population in relevant age groups. The Council is also the source of data for voting rates, benefits entitlement including free school meals, housing values, school examination pass rates and many other useful social indicators.

The Unit produced a report into area-based deprivation or ‘Areas of Stress’ ⁶ back in 1993, combining a range of Census and other variables. Part of the evolution of the Web site will be to replicate this form of analysis using an extended list of updated data. The Council’s Economy and Investment Unit have been compiling data under a range of ‘domain’ headings including Crime, Health, Housing, Education, Economic, Income, Participation and Physical Environment. An overall index of deprivation will also be calculable. This comprehensive range of quality assured and referenced datasets will shortly be available for area-based analysis in tandem with the latest population denominators on the Web-site.

3.3 Data from other agencies

Other agencies are also contributing data. A multi-agency ‘Data Sharing Group’ was set up in early 2000 and has met with enthusiasm and support. Through this group, procedures and protocols are being agreed to bring about the sharing of data between a range of agencies including all Council departments, the Police Service, Fire Service, Health Authority, Probation Service, Employment Service. The promise of the Web-site is providing a tangible focus which is helping to overcome the culture of separatism between such organisations, in line with change in the Political environment. Data will be publicly released and shared in a manner agreed in advance with each organisation.

3.4 Quality

The aim is to provide the user with good quality data, but what exactly is ‘good’ information and what is a quality information system? It is considered that a system providing quality information should be:

· Accessible – both physically and intellectually

· Replicable – both by different people, but also over time

· Dynamic – output tables will update dynamically in response to changes made to the area definition

· Authorised / official - the user needs to be confident that the data supplied is the authorised up to date version. Metadata (see Section 5.2.3) will enable this confidence

· Standardised / comparable – through the use of a standard procedure for extracting data enables meaningful comparison between outputted tables

· Joined-up - encompassing multiple data sources in an integrated ‘one-stop’ resource

Above all the data should be USEFUL. Usefulness will depend on the nature of the enquiry, but the main prerequisite is that it should be ‘fit for purpose’. The flexibility of the Web-site will assure that it meets the needs of a whole range of different applications.

4.0 The Evolution of the project

4.1 Concept and Vision

Our vision was that the provision of data could be enabled via a geographical interface contained within a Web-browser. To help to visualise this proposal, a mock-up was initially produced using Powerpoint combined with screenshots from our desktop GIS (ArcView) and which set out a ‘wish list’ of desired content and functionality. This proved to be a useful model, both to help conceptualise the project, and also to demonstrate the principle to others and so achieve backing for the project.

In parallel, available Web-based GIS software packages were evaluated. The principal requirement was functionality which would enable the user to define their own geographical area remotely over the Web and that this ‘shape’ could then be used to select other spatial data held within the Web-site (data consolidated to data points using the technique outlined below). Autodesk Mapguide was selected and purchased in August 1999 as the Web software for the project.

4.2 Technical challenges

People are very seldom interested in the abstract Enumeration District (ED) boundaries themselves – these simply provide the framework which holds the Census counts. This framework is however, a constraint on users being able to obtain data for what they recognise as their locality / community area. We therefore wanted to remove all reference to abstract ED boundaries from the process of defining custom areas. (The same applies to electoral and postal boundaries. The process is described here for EDs for simplicity and because it is relevant to Census and population estimates in Bradford).

4.2.1 Automating the task of splitting EDs

Problem: A user’s area of interest is unlikely to respect administrative boundaries, still less, the arbitrary boundaries such as Census EDs. Consequently, it is necessary to split and group such standard areas in order to estimate only that proportion of the data which falls within the user-defined area.

Splitting of EDs can be a painstaking task because of the need to take account of the distribution of residential property, not just the area proportions of the split ED (for instance, an ED might be split 50:50 by area, however 100% of the population of that ED might actually reside in one half of the ED). Indeed, many Census users would hesitate to split EDs for bespoke area definition because of the potential pitfalls in apportioning the population appropriately (i.e. in accordance with the actual distribution of households on the ground). Certain limitations cannot be overcome, such as the fact that since we do not in reality, live on a homogenous ‘isotropic plane’, Census variables will not be evenly distributed geographically and there will be natural concentrations of types of individual and household within any ED. This fine detail cannot be accounted for when the ED is split.

Because the task is painstaking and laborious when undertaken using maps by eye there is an inevitable trade-off between accuracy and pragmatism when dealing with regular ad-hoc Census requests which require custom area definitions and the splitting of EDs. The obvious attraction to the Council of making the customer themselves responsible for their area definition is that it saves Council officer time (see Appendix 3. for an illustration). The advantage to the customer is that they have control over the process and bring to bear valuable local knowledge in fine-tuning the boundaries.

Ultimately however the splitting of EDs by eye is highly subjective, such that even the same researcher is likely to allocate the population within a split ED differently on a second occasion. We were therefore looking to devise a mechanism which would overcome this problem.

4.2.2. Spreading the data to points

The ‘solution’ which has been devised and adopted in the current project, involves the ‘spreading out’ of the Census count for each ED in the district to the postcode ⁵ ‘centroids’ which fall within each ED. This seems to provide a simple yet elegant solution to one of the Census geographer’s enduring headaches by producing ‘boundary-free’ data which can be re-combined to form data counts for custom areas.

The initial work involved plotting the location of all the Ordnance Survey postal Address Points in the Bradford district (approximately 200,000) together with the ED boundaries using GIS. A ‘spatial join’ ² was used to link the two sets of data and to assign the appropriate ED code to each of the Address Points.

The Census counts were then spread out to the Address Points, for example if an ED had a population of 400 people and contained 100 Address Points, each point would be assigned a population of 4 persons.

(This assignment was undertaken using an SPSS routine). The same principle was used to incorporate data from a range of other data sources with geographies which were similarly translated to points.

The data can then be interrogated within a GIS by the user drawing an area or ’polygon’, selecting the points within it and summing the data in the population field. The aim is not to give users the opportunity to derive figures for areas smaller than EDs and the next version will be set up to specify a threshold minimum area / population. Testing revealed that when used to estimate data for custom defined areas containing split EDs, the result was superior in accuracy (and speed) to splitting by eye. The method also allows data from different geographies to all be processed into the user’s profile. The methodology has been proven to work, however certain concerns arose as the methodology was tested:

4.2.3 Database file size

Manipulation of a database of 200,000 Addresspoint records (each record also had stored against it, a field for each of the data variables from the population estimates and other sources) in this way proved unwieldy, even on a high specification PC. This was considered to be prohibitive to the roll-out of a more widely used solution. The second-generation application experimented with a streamlined version of the Address Point file produced in-house. This file consists of a more manageable 15,000 records, each one being a composite postcode centroid, derived by calculating the average latitude and longitude coordinates of groups of properties sharing each individual postcode ( - this has become known as the PCXY file).

A series of exercises were undertaken comparing population estimates derived using the full Address Point file, the PCXY file and traditional methods. This benchmarking revealed that the use of the smaller PCXY file led to surprisingly little reduction in the accuracy of the counts while in turn, this method proved significantly more accurate than when splitting EDs by eye. The process also demonstrated considerable time savings since the area definition and data production was self contained within the GIS rather than requiring the use of SASPAC. The Census counts allocated to each of the composite postcode centroids was weighted according to the number of properties sharing each postcode.

A decision was therefore taken to use the smaller PCXY postcode centroid file of 15,000 points as the new framework for carrying the Census, population and all other data counts, in place of the 900 EDs, 240 Polling Districts and other data geographies. Replacing the 900 EDs (etc) with 15,000 geographically referenced counts clearly allows for a finer resolution of analysis.

4.2.4 Non-residential Address Points

It was realised that a shortcoming of the original postcode based PCXY point file was that many Address Points are in fact commercial properties, and consequently it would be inappropriate to spread population data out to these points. There are a number of ways, all approximate, by which such premises can be identified and filtered out. Address Point itself includes a field containing business name (though this appears not to be complete – and of course may small businesses may also be residential properties). In future we are also considering employing the register of non-domestic rates to assist in this filtering exercise. The pilot system employs a method whereby GIS and aerial photography have been used to exclude areas of clearly identifiable commercial property (See Appendix 2.) This approach follows very much the same principle as traditionally used to split EDs by eye though with two important improvements, (i.) aerial photography provides an extra visual aid in interpreting the underlying map (ii.) the task is done once only for the whole district and future users benefit greatly from a pre-prepared standard definition of the residential proportion of all EDs.

5.0 The on-line prototype

5.1 Web-enablement

Having bench-tested the data selection technique using desktop software, the next step was to port it onto a Web browser to enable open access. At this stage the key aim was to produce a single ‘product’ integrating the different stages of data manipulation and presentation into a single application (rather than requiring the use of GIS software to extract and export the data and a spreadsheet to manipulate, summarise and format the output meaningfully and presentably).

5.2 Functionality

5.2.1 Drawing /Digitising

One of the most important tools incorporated in the Web-site is a boundary drawing or ‘digitising’ tool which enables the user to draw their chosen area on screen using the mouse, by tracing over the background map. The shape or ‘polygon’ produced is then used to select data from any of the data layers displayed. The user also has the option of being able to save their area back to the fileserver over the network, for further work at a later session. Such a tool, combined with built in reporting functionality (see below) transforms the previously limited functionality of a Web browser, from passive viewer to interactive interface.

5.2.2 Reports

The Web browser includes reports which have been written to automate and standardise the output. Buttons embedded in the browser link to programs which take the raw data selected graphically by the user on screen, analyse it, and present the output appropriately. The level of complexity of these tasks is limited only by the programming skills of the designer. Once such reports are embedded in the site, the software will take any selection of data made on screen, and ‘pour’; the data into the prepared template, undertaking summary calculations and transformations of the figures ‘on the fly’. An obvious attraction is that approved quality assured reports ensure that all users benefit from complete standardisation of output – free from operator error or irregular practices between users. We have enabled the user with tools which provide the capability to easily revise requests for information and more generally to enable data to be used in a flexible hands-on investigative manner. The process is also virtually instantaneous compared with the time previously taken exporting data between different software packages.

5.2.3 Metadata and hyperlinks

Besides working on making the user interface as intuitive and user-friendly as possible (through the simplification and clarification of functionality and labelling) a formal process of recording ‘metadata’ (information about each data source) within the Web-site is being adopted which will provide invaluable on-line documentation. The user will have access to information on all datasets and boundaries included in the site, including the source, definition, date of last update etc. In addition, where appropriate, hyperlinks will be built in which will link to other Web-sites (e.g. ONS home page, CBMDC Policy & Research Unit e-mail etc). The concept is therefore one of loading the application with all the necessary help and referencing to enable the non-technical user to navigate round it easily and to be able to seek further personal assistance if necessary.

By controlling the look and functionality of the site to display and describe data appropriately, expertise can be shared with the lay user, while not giving them ‘too much rope’. Untrained use of GIS can certainly otherwise lead to misinterpretation of data ³.

5.3 Benefits

Mapping the data on screen allows the user to see ‘hot spots’ or adjacent areas of similar characteristics. Traditional tabular summary of data does not allow for such spatial grouping to be easily identified – especially since neither ED nor postcode numbering is sequential one cannot assume that sequentially numbered units are actually adjacent. Another very powerful additional benefit of the GIS functionality is the visual correlation of different datasets which is achieved by geographical display (for example, by overlaying data such as unemployment and standard Mortality Ratios overlapping concentrations are evident). A simple report can answer the question - ‘what is the population of this area?’ but by using population data in tandem with other datasets, the system enables more sophisticated enquiries, such as ‘what is the population, and what is the proportion of burglaries per head of population compared to the District average?’ In Bradford, such a degree of analysis would have previously been beyond even the most skilled researcher let alone the lay user for the practical reason that prior to this initiative, the necessary datasets were not consolidated in one place, and neither did they share a common geography because of different administrative areas and levels of aggregation.

We have on the one hand devised a technique which enables us to spread out data for any local administrative area to the postcode PCXY points within it. In parallel with these developments in theory and technology, we have been making practical progress towards consolidating multi-agency data centrally to enable truly joined-up analyses.

The trade-off between time spent ‘authoring’ information on the Web-site compared to handling requests ‘manually’ is an area which will be monitored over the coming months. It should be remembered however that the end product will hopefully be greatly improved in terms of immediate access of customer to the data, but in particular, the wealth of different information which will be accessible and the degree of flexibility with which users will be able to select their area of interest (both spatially and contextually).

A closely related spin-off from the original research has been the setting up of ‘Bradford Community Statistics Project’ – a partnership, part funded by the ERDF, between Bradford Resource Centre, The Council and a range of other agencies. This project is aimed at facilitating the critical and effective use of community information by community groups to assist with funding bids, the development of local and District-wide regeneration strategies. The lead role of the Bradford Resource Centre (an umbrella for

funded and non-funded community organisations) will ensure that the evolving statistical resource is determined by the needs of the community.

The remit of the project is extending to meet a number of wider corporate requirements for the Council to share data more openly internally in the interests of promoting best practice and best value, and to share information with the citizens of Bradford in the interests of openness, transparency and community involvement and the democratisation of local government. To this end we envisage that the project will play a central role in Bradford addressing Central Government’s ‘Modern Local Government Agenda’ ⁸.

6.0 Next Steps

6.1 Security and confidentiality

An important further consideration before any roll-out of the pilot system can proceed is the need to ensure appropriate security and to protect data confidentiality. Again, the Web-based technology is an attractive alternative to the traditional alternative of proliferating copies of databases around the council to desktop PCs in insecure offices and with comparatively open access. The file server for the project is by contrast, physically located in a high security area. In addition, the software allows for a high degree of control over security of access to the data itself. Only aggregated non-personal data will be made available as standard datasets. Access to additional potentially more sensitive data will be controlled via a regulated system of user passwords. The system is also set up to ‘time-out’ after a small number of minutes so that in the event of an authorised user leaving their PC unattended, their password would need to be reintroduced after a time for continued access. The incorporation of relevant metadata will also help to ensure that the data itself is used appropriately and interpreted correctly by the user. Because many of the datasets will have been resolved to postcodes, there is a risk that a user might intentionally select two largely overlapping areas and subtraction or ‘differencing’ their profiles, extract data for a single postcode – perhaps containing only one property. Use of the PCXY file rather than the full postcode file does introduce a level of anonymity to the data since it no longer appears to be property-specific when viewed against a map background. We may however in future reinforce this by rounding results, although confidentiality will be further protected once the data seed-point layer itself rendered invisible (this is not presently possible in the standard software but we hope to have it specifically programmed for the project).

6.2 Data structures

A considerable investment needs to be made in rationalising the database structures and protocols used. The prototype operates using a small number of Access databases, whereas the longer term option may well be to use SQL Server and most definitely be to use many linked data tables rather than the use of a smaller number of cumbersome ‘flat files’.

6.3 Licencing

At present, the web-site incorporates Ordnance Survey (OS) maps and boundary files. The Council Service Level Agreement with the OS does not extend beyond internal usage without incurring royalty payments. Since maps are an essential component of the application and we are advised that the licence fees for Internet deployment of OS data would be prohibitive, we are looking into the procurement of maps and administrative boundaries which can be served on the Internet free from royalties.

7.0 Summary

The extraction of small area statistics has long been the preserve of the data specialist because of the high level of expertise required, the need for specialist software (C91, SASPAC) and above all, the prohibitive data cost. The current project has taken considerable strides to free the lay user from such traditional constraints on open access to demographic data. Further scrutiny will reveal how well we have actually addressed concerns expressed as to the suitability of GIS for demographic analysis ¹.

It is envisaged that the prototype site will be the catalyst for progressing the joining up of information systems across the council and beyond. A Working Group will shortly be making recommendations to senior management with respect to a programme for adopting a BS7666 compliant land and property gazetteer. With this place there will be the opportunity for all person / property based databases in the Council to be linked through shared unique property referencing. This in turn will provide the data infrastructure and potential for any of the Council’s service data to be made available through the on-line resource, to service planners and strategic planners alike, and for all of this to be viewed in the context of the underlying demography of any given locality and in relation to data from other agencies.

The project satisfies a mutuality of interest between the Council and the customer therefore we hope that we are consequently presiding over a win-win situation whereby both will benefit - ourselves from fewer mundane time-consuming ad-hoc queries and duplicated effort – the customer meanwhile benefiting from data being made available openly, flexibly and immediately – not delayed by the competing priorities of council officers. It is also clearly in the interest of Bradford district as a whole if the provision of on-line access to such a tool can help facilitate successful bids which will bring valuable regeneration resources into the district.

Making the Census and other official data, open and relevant to the wider community can only help to raise public awareness of, and hopefully improve compliance with, data collection. There may be further positive spin-offs in terms of enhancing the public image of the Council achieved through its clear commitment to openness and increased local democracy. Overall, the project clearly demonstrates the usefulness of small area statistics and is actively extending this usefulness beyond academic and specialist use, into the public arena.

Ref: manpaper9.doc, 14/8/00

References.

1. Dale, A; Marsh, C. eds (1993) ‘The 1991 Census User’s Guide’, Chapter 9

HMSO

2. ESRI (1996) ‘Using ArcView GIS’, Chapter 13

Environmental Systems Research Institute, Inc.

3. Monmonier, M. (1991) ‘How to lie with maps’

University of Chicago Press

4. Policy Action Team 18 (2000) Working Paper: ‘A Geographic Referencing Framework for Monitoring Local Social Conditions’

Cabinet Office

5. Raper, J; Rhind, D; Shepherd, J. (1992) ‘Postcodes: The New Geography’

Longman Scientific and Technical

6. Research Section, Chief Executives Department (1993) ‘Areas of Stress within Bradford District’

City of Bradford MDC

7. Simpson, S and Norman, P (1998) ‘Case Study: Apportionment using counts of patients and electors’

pp 61-68 in Simpson, S. ed. (1998) ‘Making Local Population Statistics: A Guide for Local Practitioners’

Local Authorities Research and Intelligence Association

8. White Paper (July 1998): ‘Modern Local Government – In Touch with the People’

DETR

Appendix 1. Creating ‘boundary –free data

Fig 1. Illustrates the problem of mis-matching user-defined boundaries and ED boundaries. The best fit achieved using standard GIS results in a definition which both incorrectly excludes some of the chosen area, while including areas beyond the desired boundary since they form part of whole EDs.

Fig 1.

Fig 2. Demonstrates how, by contrast, using data spread to postcode controids enables a much closer approximation when selecting data

Fig 2.

A polygon drawn over point-source data….. …selects only the points falling within it

Fig 3. Illustrates a selection of PCXY data seed-points achieved using GIS

Fig 3. (Screenshot from pilot ArcView application

Appendix 2.

Fig 4. Demonstrates an example of an ED where the ED boundary and the residential concentrations areas are actually very different

Fig 4.

i. ED Extent ii. Residential extent

The current prototype attempts to address this by using a ‘mask’ of residential areas (prepared with the aid of detailed maps and aerial photography) to select only those Address Points which fall in residential areas. This automates the task of ensuring that residential population is not ascribed to non-residential areas of EDs.

Appendix 3. The Mapguide prototype

Fig 5. Screenshot: Prototype Graphical User Interface (GUI)

Fig 6. Screenshot: Zoomed in with user-defined area drawn

Fig 7. Screenshot: Sample draft population report (extracted using Fig 6. user area)

Fig 8. Screenshot: other data layers switched on (locality information and Council-owned property)

Appendix 3. ‘The old way of working’: a real-world scenario

A member of the public phones the Unit to request population for ‘Keighley’. The immediate problem faced is in agreeing the definition of the area for which the data is being requested. Does the caller have an official administrative area in mind or something less straightforward?

For example, does the caller require data for Keighley Constituency? one of, or a combination of the three Keighley Wards (West, North and South). Other possibilities include a number of Neighbourhood Forum boundaries describing the area as well as other administrative areas, e.g. Parishes, Housing Management Areas, Social Work patches.

One frequently finds that the caller is not in fact sure of the their area definition once faced with such alternatives! however in this case let us assume that it transpires that what the caller actually wants is their own customised definition of the extents of their local community.

The next stage is therefore most commonly for the individual to draw their required boundary on a base map (for example, photocopied from their A-Z). The researcher must then translate this into the Census geography by transferring the boundary onto the 1:10,000 OS map base with the ED boundaries illustrated. Experience tells us that the requested area will never fall neatly onto a single map sheet but is more likely to overlap four!

Having struggled with the 1:10,000 maps on the photocopier and taped the copies together and transcribed the required boundary (not always easy if the map base / scale is different and the thickness of the pen lines on the original equate to quarter of a mile on the ground!), the researcher is now ready to extract the list of EDs covered by the area. This will entail an inevitable level of guestimate of the proportion of split EDs which ought to be included. The skilled researcher has a good eye for interpreting the underlying map so as to apportion the residential population sensibly and account for both open space and obvious commercial areas (local knowledge and a keen eye may also allow for some weighting to be allowed for concentrations of residences such as flats). This culminates in the ED definition of the bespoke area which is then input into SASPAC as a ‘gazetteer file’ in order to extract the required census counts for the area. Even then, these must be formatted into a presentable format for dissemination, commonly using spreadsheet and word-processing software.

This process has taken half a day of officer time and an eventual turn-round time of a week form initial request to return of the data. It has been a labour intensive one-off piece of work and the final output is static and not easily updated.

Two days later the individual calls again – having received the maps and data produced, they have realised an error in the boundary they defined, therefore can you adjust the figures to the new boundary?!