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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.
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.
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:
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.
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.
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 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.
Research carried out at the University of Leeds has been used to develop data sets that are now routinely used in offshore oil exploration to identify prospective areas faster, and with reduced cost. New techniques applied to satellite altimeter data have been used to compute gravity anomalies in marine areas with increased accuracy and reliability relative to earlier products. These anomalies have been developed during the REF period in association with a University of Leeds spin-out company (Getech) into a global data set, which has been sold and licensed extensively within the hydrocarbon exploration industry. The global data set has delivered economic and reputational benefits to Getech, and has been employed by oil companies in more than 50 exploration projects per year. Shell values the improved gravity data at $2.5M per project.
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.