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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.
The advanced information management research of the Department of Digital Humanities (DDH) has led to a better understanding of pollution processes in inland waterways and lakes. It has also improved the standard of water quality information that is available to government and regulatory authorities. The information management framework which DDH has provided supports government-funded activities to improve environmental standards and has helped ensure that the UK Environment Agency is able to comply with the EU's Water Framework Directive, reducing the risk of financial penalties for non-compliance. Moreover, key and accurate evidence about water quality has been made freely available to beneficiaries, including governmental and non-governmental agencies, farmers and land managers, and the general public.
The North East Economic Model (NEEM) was designed and developed at Durham University Business School (DUBS) from 2003. Customized to the regional economy, the aim of the research was for NEEM to model intra- and extra-regional economic relationships to provide quantitative estimates/projections of the impact of both long-term economic trends and shorter-term economic `shocks'. Its application has had significant impacts on policy practitioners in the region by: (1) facilitating more robust evidence-based policy analysis; (2) giving rise to knowledge transfer to policy-makers regarding the structure and workings of the regional economy; and (3) acting as a catalyst for an extended regional policy-modeling capacity. By influencing professional practice, it has had demonstrable impacts on regional economic policy, regional economic restructuring and local planning.
Dr Walmsley has worked on numerous studies relating to the concept of Corporate Social Responsibility (CSR) relating to the tourism and hospitality sector. The research that forms the basis for this case study was commissioned by the organisation `International Consumer Research and Testing' on behalf of its members. The purpose was to inform consumers about the impacts of tourism, influence their selection of hotel groups and investigate different corporate policies and practices. The hope, on the part of the commissioning organisation, was that consumer pressure would challenge and change industry behaviour. In terms of providing information on CSR performance the hope was that this would benefit the hotels themselves by providing a common method of assessment.
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.
KCL research played an essential role in the development of data provenance standards published by the World Wide Web Consortium (W3C) standards body for web technologies, which is responsible for HTTP, HTML, etc. The provenance of data concerns records of the processes by which data was produced, by whom, from what other data, and similar metadata. The standards directly impact on practitioners and professional services through adoption by commercial, governmental and other bodies, such as Oracle, IBM, and Nasa, in handling computational records of the provenance of data.
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.
The research at the University of Reading has developed statistical methods and information systems for two global monitoring systems for elephants: MIKE (Monitoring the Illegal Killing of Elephants) and ETIS (Elephant Trade Information System). The systems provide quantitative evidence, via bias-adjusted indicators, on global and regional trends in the illegal killing of elephants and the illicit ivory trade. This evidence forms the substance of reports discussed at the Convention for International Trade in Endangered Species of Wild Fauna and Flora (CITES). Based on this information, CITES has adopted decisions to introduce interventions targeting over 20 countries in Africa, Asia and the Middle East aimed at curbing the illegal ivory trade. As well as providing the underpinning data that has informed international policy on illicit trading of this threatened species, the evidence has also helped raise public awareness of the threats to elephants as well as improving monitoring systems and increasing their reach.
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.
We have influenced the development and implementation of national higher education policies and educational practices in Scotland as well as international policies through the development of a distinctive approach to evaluation based on social practice theory. Using a novel way of conceptualising and conducting evaluative research, we have: