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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

Case Study 5: Knowledge Management Technology for Pharmaceutical and Healthcare Industries (InforSense)

Summary of the impact

The research in this case study has pioneered knowledge management technology. It has had major impact on drug discovery and translational medicine and is widely adopted in the pharmaceutical and healthcare industries. The impacts are:

  1. The formation of InforSense to commercialise the technology. The company had 150 employees in June 2009 when it merged with IDBS Ltd to create the world's second largest life science informatics company.
  2. The results from knowledge management technology and associated software platform have enabled the integration of molecular, imaging, clinical data and analytics, to identify biomarkers for disease identification, treatment selection and side effect prediction.
  3. Since 2002 the technology has been deployed by major pharmaceutical companies (including GSK, AZ, Roche, Pfizer, Bayer and Boehringer Ingelheim) and leading healthcare institutions e.g. Mayo Clinic, Harvard Medical School and King's Health Partners, generating significant social, health and economic impact.

Submitting Institution

Imperial College London

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Computation Theory and Mathematics, Distributed Computing, Information Systems

Freshwater Information Management and Data Sharing to Meet Environmental Standards

Summary of the impact

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.

Submitting Institution

King's College London

Unit of Assessment

Communication, Cultural and Media Studies, Library and Information Management 

Summary Impact Type

Environmental

Research Subject Area(s)

Information and Computing Sciences: Information Systems
Economics: Applied Economics

Informatics support for the management and integration of large-scale life sciences data

Summary of the impact

Research carried out at Birkbeck's Department of Computer Science and Information Systems since 2000 has produced techniques for the management and integration of complex, heterogeneous life sciences data not previously possible with large-scale life sciences data repositories. The research has involved members of the department and researchers from the European Bioinformatics Institute (EBI) and University College London (UCL) and has led to the creation of several resources providing information about genes and proteins. These resources include the BioMap data warehouse, which integrated the CATH database — holding a classification of proteins into families according to their structure, the Gene3D database — holding information about protein sequences, and other related information on protein families, structures and the functions of proteins such as enzymes. These resources are heavily utilised by companies worldwide to explore relationships between protein structure and protein function and to aid in drug design.

Submitting Institution

Birkbeck College

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Computation Theory and Mathematics, 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

Linking Archaeological Data - enabling semantic infrastructure in the digital archaeology domain

Summary of the impact

Our research has enabled archaeological professional and commercial organisations to integrate diverse archaeology excavation datasets and significantly develop working practices. Commercial archaeological datasets are usually created on a per-site basis structured via differing schema and vocabularies. These isolated information silos hinder meaningful cross search and comparison. As the only record of unrepeatable fieldwork, it is essential that these data are made available for re-use and re-interpretation. As a result of the research, the Archaeology Data Service, English Heritage, the Royal Commissions on the Ancient and Historical Monuments of Scotland and Wales have published as Linked Data important excavation datasets and national vocabularies that can act as hubs in the web of archaeological data.

Submitting Institution

University of South Wales

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Cultural

Research Subject Area(s)

Information and Computing Sciences: Data Format, Information Systems
History and Archaeology: Archaeology

Data provenance standardisation [DPS]

Summary of the impact

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.

Submitting Institution

King's College London

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Computer Software, Information Systems

Intelligent Systems incorporating Automatic Classification and Carbon Footprinting for Corporate E-Procurement

Summary of the impact

Two Knowledge Transfer Partnership projects, carried out between 2006 and 2009, between an e-commerce marketplace provider (@UK plc) and the University of Reading, led to the development of two software tools that were launched in 2010. The tools, SpendInsight and GreenInsight, are the first of their kind to use artificial intelligence techniques to handle the extremely challenging data associated with purchasing in large organisations. Since their launch, these tools have been used by @UK plc to identify procurement savings and environmental costs of procurement activities for governments, multi-national corporations, academic institutions and healthcare providers. Over the last three years @UK plc has benefitted from the launch of these products as it has provided them with a competitive advantage over the market place, increased the quality and efficiency of their spend analyses and led to multi-million pound licensing agreements. An analysis of spending in some of the NHS Trust Foundations has led to changes in procurement behaviours that have resulted in hundreds of thousands of pounds saved to date — benefitting not only the NHS, but also taxpayers.

Submitting Institution

University of Reading

Unit of Assessment

Electrical and Electronic Engineering, Metallurgy and Materials

Summary Impact Type

Economic

Research Subject Area(s)

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

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