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Research by the University of Southampton has led to an entirely new approach to the creation and management of small geographical areas for the publication of official statistics, including those from the 2001 and 2011 UK Censuses and the Neighbourhood Statistics Service. The software at the heart of this transformation is now used in 10 countries, while the academics responsible for it have helped inform government decisions, are integral to the policy and practice of the Office of National Statistics and have presented evidence to various influential committees. The research continues to deliver benefits to a large user community.
The Scottish Longitudinal Study (SLS) is a pioneering study, combining census, civil registration, health and education data (administrative data). It has established an approach that allows the legal and ethical use of personal, sensitive information by maintaining anonymity within the data system. This approach has become a model for the national data linkage systems that are now being established across the UK. The SLS has also enabled policy analysts to monitor key characteristics of the Scottish population in particular health inequalities (alerting policy makers to Scotland's poor position within Europe), migration (aiding economic planning) and changing tenure patterns (informing house building decisions). Finally, the study has become fully embedded in Scotland's National Statistical agency, allowing it to produce new informative statistical series.
Statistical techniques developed at the University of Southampton have transformed the accuracy with which Census data can estimate the UK population's size and characteristics, delivering far-reaching socio-economic impact. The methodologies developed by Southampton have increased the accuracy and availability of the 2011 UK Census data, not only for the Office for National Statistics but for central government, local authorities, the NHS and the private sector, who all use the data as a basis for policy decisions. Preserving the privacy of the UK population, Southampton's work allowed, for the first time, the release of highly localised data, which is used by local authorities to target resources efficiently and meet the demands imposed by the Localism and Equality Acts.
There is growing evidence that official population statistics based on the decennial UK Census are inaccurate at the local authority level, the fundamental administrative unit of the UK. The use of locally-available administrative data sets for counting populations can result in more timely and geographically more flexible data which are more cost-effective to produce than the survey-based Census. Professor Mayhew of City University London has spent the last 13 years conducting research on administrative data and their application to counting populations at local level. This work has focused particularly on linking population estimates to specific applications in health and social care, education and crime. Professor Mayhew developed a methodology that is now used as an alternative to the decennial UK Census by a large number of local councils and health care providers. They have thereby gained access to more accurate, detailed and relevant data which have helped local government officials and communities make better policy decisions and save money. The success of this work has helped to shape thinking on statistics in England, Scotland and Northern Ireland and has contributed to the debate over whether the decennial UK Census should be discontinued.
Coombes' research to advance spatial-analysis methodology has re-defined Travel-to-Work Areas (TTWAs) — the only official UK boundaries defined by academics — and produced three distinct strands of impact.
New visualisation approaches have been used to turn complex data into actionable knowledge by:
These applications of new visualisation methods have had impact on the environment, economy, defence and security, society and public debate. In each case users of our methods report on their positive impact as we help them identify visualisation possibilities, understand their data and use this knowledge to inform their activity. In many cases our work has resulted in important insights, improved exploitation of data and further investment in visualisation with organisational implications in terms of using data for intelligence.
The impact relates to improved productivity, operational efficiency, working practice and knowledge management within the European maritime industry through the use of a Virtual Integration Platform (VIP). The platform is a software package developed within the University of Strathclyde that has been used by eleven European ship design, engineering and project management consultancies, which specialise in the application of advanced computational design, analysis and physical modelling techniques within projects on an international scale. Specific company benefits of using the VIP include: 67% reduction in process time; guaranteed data consistency; additional productivity of 15 hours/day from automated over-night operation; capturing and reuse of expertise; cost effectiveness (lack of data consistency typically costs €100k per project); and ease of operation within complex design processes.
Targeted Projection Pursuit (TPP) — developed at Northumbria University — is a novel method for interactive exploration of high-dimension data sets without loss of information. The TPP method performs better than current dimension-reduction methods since it finds projections that best approximate a target view enhanced by certain prior knowledge about the data. "Valley Care" provides a Telecare service to over 5,000 customers as part of Northumbria Healthcare NHS Foundation Trust, and delivers a core service for vulnerable and elderly people (receiving an estimated 129,000 calls per annum) that allows them to live independently and remain in their homes longer. The service informs a wider UK ageing community as part of the NHS Foundation Trust.
Applying our research enabled the managers of Valley Care to establish the volume, type and frequency of calls, identify users at high risk, and to inform the manufacturers of the equipment how to update the database software. This enabled Valley Care managers and staff to analyse the information quickly in order to plan efficiently the work of call operators and social care workers. Our study also provided knowledge about usage patterns of the technology and valuably identified clients at high risk of falls. This is the first time that mathematical and statistical analysis of data sets of this type has been done in the UK and Europe.
As a result of applying the TPP method to its Call Centre multivariate data, Valley Care has been able to transform the quality and efficiency of its service, while operating within the same budget.
Open Data has lowered barriers to data access, increased government transparency and delivered significant economic, social and environmental benefits. Southampton research and leadership has led to the UK Public Data Principles, which were enshrined in the UK Government Open Data White Paper, and has led to data.gov.uk, which provides access to 10,000 government datasets. The open datasets are proving means for strong citizen engagement and are delivering economic benefit through the £10 million Open Data Institute. These in turn have placed the UK at the forefront of the global data revolution: the UK experience has informed open data initiatives in the USA, EU and G8.
Small area estimation (SAE) describes the use of Bayesian modelling of survey and administrative data in order to provide estimates of survey responses at a much finer level than is possible from the survey alone. Over the recent past, academic publications have mostly targeted the development of the methodology for SAE using small-scale examples. Only predictions on the basis of realistically sized samples have the potential to impact on governance and our contribution is to fill a niche by delivering such SAEs on a national scale through the use of a scaling method. The impact case study concerns the use of these small area predictions to develop disease-level predictions for some 8,000 GPs in England and so to produce a funding formula for use in primary care that has informed the allocation of billions of pounds of NHS money. The value of the model has been recognised in NHS guidelines. The methodology has begun to have impact in other areas, including the BIS `Skills for Life' survey.