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4 Structural Science – Equipment and Software for Industry

Summary of the impact

Durham Chemistry has a long history of research in cutting edge crystallographic methods and innovative instrument design which has led to the commercialisation of scientific apparatus and software with significant sales value. Durham-developed apparatus and crystallographic software are used globally by both industry and academia. Autochem2, for example, is sold exclusively to Agilent via the spin-out company OlexSys, and hundreds of researchers rely on Durham's contributions to the Topas software pacakge. Crystallographic research for pharmaceutical and other companies, research-based consultancy, commercial analytical services and provision of international PhD+ level training schools have led to further significant impact.

Submitting Institution

University of Durham

Unit of Assessment

Chemistry

Summary Impact Type

Technological

Research Subject Area(s)

Physical Sciences: Other Physical Sciences
Chemical Sciences: Inorganic Chemistry, Physical Chemistry (incl. Structural)

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

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

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

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

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

The DichroWeb Analysis Server and Protein Circular Dichroism Data Bank: analysis tools for structural biology

Summary of the impact

DICHROWEB is a comprehensive, user-friendly server that provides access to computational tools for the determination of protein secondary structure from data obtained through circular dichroism (CD) and synchrotron radiation (SRCD) spectroscopy. The Protein Circular Dichroism Data Bank (PCDDB) is a database of spectra obtained using these techniques and allied data. Both resources are widely and increasingly used in many countries and are proving useful in industrial research (for example, in drug discovery) as well as academia and advanced teaching. DICHROWEB currently has over 3,600 registered users and over 375,000 DICHROWEB analyses have been run. Since the launch of PCDDB in 2009, the database has had over 175,000 unique hits from 41 different countries, and 89,890 downloads.

Submitting Institutions

University College London,Birkbeck College

Unit of Assessment

Biological Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Biological Sciences: Biochemistry and Cell Biology
Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

Impact of Machine-Learning based Visual Analytics

Summary of the impact

Visual analytics is a powerful method for understanding large and complex datasets that makes information accessible to non-statistically trained users. The Non-linearity and Complexity Research Group (NCRG) developed several fundamental algorithms and brought them to users by developing interactive software tools (e.g. Netlab pattern analysis toolbox in 2002 (more than 40,000 downloads), Data Visualisation and Modelling System (DVMS) in 2012).

Industrial products. These software tools are used by industrial partners (Pfizer, Dstl) in their business activities. The algorithms have been integrated into a commercial tool (p:IGI) used in geochemical analysis for oil and gas exploration with a 60% share of the worldwide market.

Improving business performance. As an enabling technology, visual analytics has played an important role in the data analysis that has led to the development of new products, such as the Body Volume Index, and the enhancement of existing products (Wheelright: automated vehicle tyre pressure measurement).

Impact on practitioners. The software is used to educate and train skilled people internationally in more than 6 different institutions and is also used by finance professionals.

Submitting Institution

Aston 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, Computation Theory and Mathematics, Information Systems

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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