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Leading the open data revolution

Summary of the impact

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.

Submitting Institution

University of Southampton

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Political

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Information Systems

The application of embedded analytics to hyper-scale and distributed data archives

Summary of the impact

The research improves digital data archives by embedding computation into the storage controllers that maintain the integrity of the data within the archive. This opens up a number of possibilities:

  • Data analysis can be automated and incorporated into the archiving process;
  • The approach improves the archiving of all types of digital objects, from television broadcasts to genomes;
  • The approach can be applied to distributed data and to datasets that are too big for traditional approaches.

This has impact on three different classes of beneficiary:

  • Providers of national data infrastructure in the UK and US, who are incorporating Cheshire 3 into national data repositories;
  • Data Users, such as Astra Zeneca, RAI, Sanger Institute, who are using Cheshire 3 to extract valuable information from their data;
  • Equipment vendors, such as NetApp, Xerox and Bellerophon Mobile, who are developing commercial systems that will use Cheshire 3.

Submitting Institution

University of Liverpool

Unit of Assessment

Communication, Cultural and Media Studies, Library and Information Management 

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

Improving Social Care Call Centre Operational Effectiveness

Summary of the impact

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.

Submitting Institution

Northumbria University Newcastle

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

Estimating local populations with far greater accuracy using administrative data

Summary of the impact

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.

Submitting Institution

City University, London

Unit of Assessment

Business and Management Studies

Summary Impact Type

Political

Research Subject Area(s)

Medical and Health Sciences: Public Health and Health Services
Economics: Applied Economics

Sustainable Growth for Farming and Small Food Businesses through the use of Consumer Insight

Summary of the impact

Prof. Andrew Fearne's consumer insight research project influenced marketing practice in almost 400 farming and small food businesses, while helping eight food industry associations and regional development agencies meet their remits. It also supported local supplier initiatives at the UK's largest supermarket, Tesco. A recent participant survey showed that 89% of farmers and small food producers who engaged with the project found that the consumer insight was either `quite' or `extremely useful'. Meanwhile, the project helped Tesco grow its sales of local food and drink from £0.5 billion (2005) to over £1 billion (2012) against average retail sales growth of less than 5% per year over the same period (Office of National Statistics).

Submitting Institution

University of Kent

Unit of Assessment

Business and Management Studies

Summary Impact Type

Economic

Research Subject Area(s)

Economics: Applied Economics
Commerce, Management, Tourism and Services: Business and Management, Marketing

Development of bioinformatics techniques leads to biomarker discovery and realisation of commercial potential

Summary of the impact

The research led by Professor Graham Ball at Nottingham Trent University has developed new bioinformatics techniques for mining complex post genomic bio-profile data. The approach allows development of predictive models to answer clinical questions using an optimum biomarker panel. The impact of this work is through the filing of four patents associated with algorithms, breast cancer and tuberculosis, subsequently licensed to a spin-out company. To date three clinical trials have been supported with others in the pipeline. Through the spin-out company the approach is being applied to stratify patients in clinical collaborations and to optimise biomarker panels for diagnostics companies.

Submitting Institution

Nottingham Trent University

Unit of Assessment

Allied Health Professions, Dentistry, Nursing and Pharmacy

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Biological Sciences: Genetics
Information and Computing Sciences: Artificial Intelligence and Image Processing

Improving Data Models in Operational IT Systems

Summary of the impact

The impact of this work stems from the provision of better quality information models, and is manifest via: (a) reduced cost through improved reuse and less rework; (b) improved system interoperability; and (c) enhanced assurance and checking that information requirements are supported by the resultant systems. The approach has been applied in commercial environments, such as Shell (UK), where it has reduced development costs by up to 50% ($1m in one case). It has also been applied in the defence environment, forming a part of underpinning standards currently being implemented by the UK and Swedish Armed Forces.

Submitting Institution

Brunel University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

CCPN: A novel approach to data exchange between software applications

Summary of the impact

Researchers in Cambridge have developed a data standard for storing and exchanging data between different programs in the field of macromolecular NMR spectroscopy. The standard has been used as the foundation for the development of an open source software suite for NMR data analysis, leading to improved research tools which have been widely adopted by both industrial and academic research groups, who benefit from faster drug development times and lower development costs. The CCPN data standard is an integral part of major European collaborative efforts for NMR software integration, and is being used by the major public databases for protein structures and NMR data, namely Protein Data Bank in Europe (PDBe) and BioMagResBank.

Submitting Institution

University of Cambridge

Unit of Assessment

Biological Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Computer Software, Information Systems

Establishing a blueprint for administrative data based longitudinal studies in the UK

Summary of the impact

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.

Submitting Institution

University of St Andrews

Unit of Assessment

Geography, Environmental Studies and Archaeology

Summary Impact Type

Political

Research Subject Area(s)

Mathematical Sciences: Statistics
Medical and Health Sciences: Public Health and Health Services
Economics: Applied Economics

The use of multilevel statistical modelling has led to improved evidence-based policy making in education and other sectors

Summary of the impact

Since 2008, statistical research at the University of Bristol has significantly influenced policies, practices and tools aimed at evaluating and promoting the quality of institutional and student learning in the education sector in the UK and internationally. These developments have also spread beyond the education sector and influence the inferential methods employed across government and other sectors. The underpinning research develops methodologies and a much-used suite of associated software packages that allows effective inference from complicated data structures, which are not well-modelled using traditional statistical techniques that assume homogeneity across observational units. The ability to analyse complicated data (such as pupil performance measures when measured alongside school, classroom, context and community factors) has resulted in a significant transformation of government and institutional policies and their practices in the UK, and recommendations in Organisation for Economic Co-operation and Development (OECD) policy documents. These techniques for transforming complex data into useful evidence are well-used across the UK civil service, with consequent policy shifts in areas such as higher education admissions and the REF2014 equality and diversity criteria.

Submitting Institution

University of Bristol

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Societal

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Computation Theory and Mathematics, Information Systems

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