Interaction Data: Progress and Potential John Stillwell and Oliver Duke-Williams Centre for Interaction Data Estimation and Research (CIDER) School of.

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Presentation transcript:

Interaction Data: Progress and Potential John Stillwell and Oliver Duke-Williams Centre for Interaction Data Estimation and Research (CIDER) School of Geography, University of Leeds Presentation at ‘Census 2011: Impact and Potential’ University of Manchester, 7-8 July, 2011

Acknowledgement: Support from ESRC and data providers

Presentation 1.What has CIDER achieved over the last 5 years? 2.How have the interaction data sets been used in research? 3.What potential does the 2011 Census provide for data provision and research? 4.Conclusions: How will CIDER develop in the future?

1. What has CIDER achieved over the last 5 years? 1.1 Assembly and storage of large volume of origin-destination data sets 1.2 Development of important online interface (WICID) to the Census interaction data sets 1.3 Provision of training and advice to users 1.4 Research using the interaction data sets- examples

1.1 Assembly and storage of large volume of origin-destination data sets CIDER’s audit of interaction data from various sources Censuses of Population – comprehensive, reliable migration and commuting data, particularly for flows within and between small areas Administrative records – collection of records arising from some transaction, registration or record of service delivery Social surveys – population samples allowing useful cross-classification at national (regional) level See Dennett, A., Duke-Williams, O. and Stillwell, J. (2007) Interaction data sets in the UK: An audit, Working Paper 07/05, School of Geography, University of Leeds (

CIDER’s interaction data sets Census Origin-Destination Statistics 1981 SMS Set 2 and SWS Set C (county/region level) 1991 SMS Sets 1 and 2; SWS Sets A-C (ward level) and Table 100 (students flows at district level) 2001 SMS Sets 1 and 2; SWS (levels 1-3: districts, wards, output areas in England & Wales) STS (levels 1-3 and postal sectors in Scotland) Some very large matrices CountryLevel 1Level 2Level 3 EnglandLondon Boroughs (33), Metropolitan Districts (36), Unitary Authorities (46), Other Local Authorities (239) CAS wards (7,969)Output areas (165,665) WalesUnitary Authorities (22)CAS wards ( 881)Output areas (9,769) ScotlandCouncil Areas (32)ST wards ( 1,176)Output areas (42,604) Northern Ireland Parliamentary Constituencies (18) CAS wards (582 )Output areas (5,022) TotalDistricts (426)Interaction wards (10,608) Output areas (223,060)

CIDER’s interaction data sets Census Commissioned Tables Set of tables from 2001 Census including, e.g. C0648: Migrants by religion at district level C0649: Commuters by religion at district level C0711: Migrants by ethnic group and age at district level (including all-age immigrants from different world regions of previous residence) C0723: Migrants by age and ethnic group at region/ward level C0311: Commuters to OAs in London from districts in England and Wales

CIDER’s interaction data sets Derived or estimated flows from Census data SMSGAPS: Counts for 1991 SMS Set 2 Tables 3-10 derived by Rees and Duke Williams that include estimates of suppressed values MIGPOP: Counts for 1991 SMS Set 2 Table 3 derived by Simpson and Middleton that adjust for under- enumeration 1981 SMS Set 2 (wards) and SWS Set C (wards): re- estimated for 1991 and 2001 geography by Boyle and Feng 1991 SMS Set 1 (wards) and SWS Set C (wards): re- estimated for 2001 geography by Boyle and Feng

CIDER’s interaction data sets Estimated flows based on administrative data Patient register/NHSCR flows between local authority districts in England and Wales, 19998/ /08 (rounded) – estimated and supplied by ONS Inter-NUTS2 region migration estimates for UK, 1999/2000 to 2006/2007 – estimated and supplied by Rees and Dennett (DEMIFER project) Inter-NUTS2 region migration estimates for UK, calendar year 2000 to 2007 – estimated and supplied by Rees and Dennett (DEMIFER project) Inter-region migration by age, sex and ethnicity for Britain, and estimated and supplied by Raymer and Giuletti (ESRC project) Inter-county migration by age, sex and ethnicity, , estimated and supplied by Raymer and Giuletti (ESRC project) Inter-county migration by age, sex and economic activity, , estimated and supplied by Raymer and Giuletti (ESRC project)

1.2 Development of important online interface to the Census interaction data sets CIDER Home Page Need to be a registered user of census data

WICID Query Interface

Data selection Tables available in 2001 SMS Level 1 Cells of Table 3 in 2001 SMS Level 1

Geography selection Area selection tools available List selection of districts

Map Selection Tool

Map Selection Tool (detail)

Postcode based selection

Finalise Screen Screen Indicating Extraction Completed

Example of simple query and data extracted The Query: The Query: Extract the data on total migrant flows between the countries of the UK from Table MG1010 in 2001 SMS The Data: The Data: Origin by destination matrix of migration flows in

Analysis functions for use on extracted data

Help System opening inside a new browser window

WICID User Statistics: Data extractions

1.3 Provision of training and advice to users Census Programme training workshops Classroom exercises (Stillwell, 2006b; Dennett, 2010) Bespoke support for research users – particularly those requiring large sets of data Tutorial materials (CHCC project):

2. How have the interaction data sets been used in research? 2.1 Interaction data sets used by various researchers See some examples in Part 2 of CIDER book: CIDER staff plus Boden, Boyle, Champion, Coombes, Feng, Flowerdew, Frost, Giulietti, Harland, Norman, Raymer and Rees

2.2 CIDER Research Example 1: Migration patterns based on Vickers et al. (2003) district classification Top ten directional flows and net migration rates between area clusters, Directional migration flows Directional net migration rates Source: Dennett, A. and Stillwell, J. (2010) Internal migration in Britain, , examined through an area classification framework, Population, Space and Place, 16(6):

Example 2: CIDER’s own migration-based district classification Source: Dennett, A. (2010) Understanding internal migration in Britain at the start of the 21 st century, PhD Thesis, School of Geography, University of Leeds. Forthcoming papers in Population Trends and Journal of Population Geography District classification 408 districts used 56 migration variables selected and standardised Euclidian distance used as measure of proximity k-means algorithm used for clustering Optimal solution is 8 clusters

Example 3: What processes of ethnic migration are taking place in London at ward level? Net migration flows within Net migration flows between Greater London London and rest of England and Wales Source: 2001 Census Commissioned Table Stillwell, J. (2010) Ethnic population concentration and net migration in London, Environment and Planning A, 42: Location quotients WHITES

Example 4: Changing patterns of net migration as shown by patient register/NHSCR data 2005/06 net balances Changes in net balances 2000/ /06 Source: Duke-Williams, O. and Stillwell, J. (2010) Temporal and spatial consistency, Chapter 5 in Stillwell, J., Duke-Williams, O. and Dennett, A. (eds.) (2010) Technologies for Migration and Commuting Analysis, IGI Global, pp Annual inter-district flows, 1998/ /06

3. What potential does the 2011 Census provide for data provision and research? 3.1 What has not changed since 2001 in terms of available data based on questions asked? 3.2 What about statistical disclosure control? 3.3 What new questions enable further ‘interaction’ data to be generated?

3.1 Migration question in 2011 similar to question in 2001 ‘No usual address one year ago’ excluded ….. but ‘Student term time address..’ included

Commuting question also very similar

Migration tables in SMS still under review but look as though they are going to be the same Source: ONS (2011) Proposed geographies for tables, consultations/2011-output-consultation---main-statistical-outputs---second-round/index.html

Same with commuting tables SWS/STS Source: ONS (2011) Proposed geographies for tables, consultations/2011-output-consultation---main-statistical-outputs---second-round/index.html

New geography of commuting destinations: Workplace Zones (WPZs) OAs based on where people live not work – can be unsuitable for workplace statistics Some OAs contain no/few businesses; some contain many businesses or large employer, e.g. business parks, City of London Workplace Zones project looking at splitting/merging OAs for a new geography constrained to MSOAs Pilot areas: Tower Hamlets, City of London, Southampton, Nottingham, Suffolk Coastal Disclosure control: Population threshold same as OAs (100 workers min; 625 max; no household threshold) Source: Spicer, K. (2011) Statistical Disclosure Control for 2011 UK Census, main-statistical-outputs---second-round/index.html main-statistical-outputs---second-round/index.html

3.2 What about statistical disclosure control? Small cell adjustment abandoned in favour of record swapping: - Households swapped - Targeted to ‘risky’ records - Construct risk score for every individual; combine to household score - Imputation considered as part protection - Households swapped only as far as their risk is considered ‘high’ - Individuals swapped between communal establishments Work on SDC on Origin-Destination Tables still ongoing Source: Spicer, K. (2011) Statistical Disclosure Control for 2011 UK Census, consultation---main-statistical-outputs---second-round/index.html consultation---main-statistical-outputs---second-round/index.html

3.3 What new questions enable further ‘interaction’ data to be generated? Questions 5 and 6 ask about another address Potential to produce matrices of interaction flows between usual address and other address – very useful for analyses of mobility (weekly commuting, shared custody of children, second homes, international mobility) hitherto uncaptured …… except for students

Student ‘migration’ picked up by separate questions

Questions about international immigration NB. ONS could provide immigrants by country of birth and by country of previous residence if cross-classified with Question 21

4. Conclusions: How will CIDER develop in the future? Anticipation of substantial demand for access to 2011 Census interaction data sets Continue to offer user access to data from previous censuses Recognise the ‘new’ environment – with 2011 Census being the last census of its kind Focus data from on surveys and administrative sources ONS ‘Beyond 2011’ project and Integrated Population Statistics System WICID will incorporate various non-census data sets and use same type of query interface for extraction and downloading

repository WICID will become a repository for all types of interaction data CIDER already collecting other non-census data sets on: (i) internal migration (e.g. NHS patient movement data time series from to ; HESA student flows) (ii) international data (e.g. from a series of different administrative sources including GP Flag 4 registrations; NINo registrations; HESA statistics – all at district level)

Some challenges for WICID Re-design the interface (and metadata) to present better classification of data sets – List by source as well as by theme Extending the interface to handle time-series data – Easy selection of multiple waves of data of interest – Time series analysis and summary functions Extend the range of supported geographies – Different types of geography (point locations as well as area) – Clearly display of relevant geographies Incorporation of ‘on-the-fly’ disclosure control routines for datasets like HESA – Round data after aggregation but before giving to user Improved mapping of results – Flow maps of extracted data – Choropleth maps of extracted data and analysis results

Improved data divisions

Changing access arrangements Access arrangements for 2011 Census data are not yet known – ONS concerned about disclosure risks in interaction data – There may need to be a more secure path for spatially detailed data – However, interaction data don’t necessarily fit the current security models – Open Government Data models suggest easier access to data, not harder access

The benefits of an API based system Delivery of data via an API offers close linking of values with their corresponding metadata – This should make it easier to match data items with the right populations when calculating rates Makes it easier to add new specialised aggregations as they become available Easier to re-purpose ONS data Allow WICID to become a value-adding conduit for data

ONS 2011 data repository ONS Read API Legacy Census data (CIDER) ONS 2001 data ONS pre-2001 data ? Other data sources system WICID RESTful API? WICID application

ONS web environment

Contact details John Stillwell Oliver Duke-Williams CIDER Web site: