This proposal brings together a group of leading multidisciplinary teams in medical, chemical, metabolic, statistical and computational sciences from across Imperial College London (ICL, lead institution) and its partners. These include the Institute of Cancer Research, the European Molecular Biology Laboratory-European Bioinformatics Institute, the Universities of Oxford, Swansea and Nottingham, and the MRC Clinical Sciences Centre and MRC Human Nutrition Research Centre, supported by strong partnerships and collaborative links with industry, the NHS and the National Institute for Health Research funded Biomedical Research Centres and Units. The proposal seeks support to build a DEDICATED INFRASTRUCTURE in data storage, aggregation, analysis and visualisation of diverse types of biomedical data. These come from standard clinical sources through to different types of information including from genetic analysis, and metabolic information, that help us to define patients or people studied in the general population using a holistic "systems medicine" framework. The GLOBAL AIM is to make major advances in understanding the causes and reasons for disease progression of common human diseases such as cancer, cardiovascular disease, respiratory disease and metabolic disorders such as type 2 diabetes and obesity. In this way we aim to create new disease diagnostics and prognostics aimed at the individual patient ("stratified medicine") through innovations in medical bioinformatics with powerful computing capability. The programme will create unprecedented capacity to i) DEVELOP powerful new approaches for computation and analysis of large-scale, complex, multi-source medical data; ii) INTEGRATE information linking multiple different types of biological information from analysis of blood and urine samples (e.g., metabolic, genomic, analysis of the microbial genome) to different diseases, disease progression and outcomes; hence to iii) help UNDERSTAND the causes and mechanisms of disease and improve individual disease classification for better patient treatments and safety; also to iv) TRANSFORM the training of the biomedical researchers of the future through creation of a seamless interdisciplinary environment spanning biomedicine, physical sciences, computing and engineering. In particular we will capitalise on computational expertise that has led to the development of a partnership in medical information infrastructure and service between universities and the pharmaceutical industry called eTRIKS, and related software platforms such as tranSMART, an "open source" solution for managing data and research knowledge in clinical studies. We also have world-leading expertise in metabolic "fingerprinting" and systems medicine approaches manifested in the MRC-NIHR National Phenome Centre located at ICL, and underpinned by excellence in genomics, computational sciences and advanced data modelling and visualisation. This project has a very broad collaboration with industrial sectors including major pharmaceutical companies, instrument vendors, IT and informatics companies. Our project covers the complete healthcare envelope of data generating activity and analysis from the level of basic measurement sciences through to the understanding of gene-environment interactions and disease mechanisms to the creation of knowledge systems for better clinical decision making based on detailed knowledge of individual patient biology. This application is strengthened by the decision of ICL to establish a major interdisciplinary centre for 'big data' at the new Imperial West campus, ensuring sustainability over the longer term. The project aims to deliver top class science, a robust informatics platform and in-depth scientific data and knowledge to contribute to the state of the art of UK and international medical research.

There are an estimated 50 million words in the statute book, with 100,000 words added or changed every month. Search engines and services like legislation.gov.uk have transformed access to legislation. No longer the preserve of legal professionals, law is accessed by a much wider group of people, the majority of whom are typically not legally trained or qualified. All users of legislation, from researchers in history, linguistics, lawyers, to a myriad of disciplines, are confronted by the volume of legislation, its piecemeal structure, frequent amendments, and the interaction of the statute book with common law and European law. There is a problem. Researchers typically lack the raw data, the tools, and the methods to undertake research across the whole statute book. Arts and humanities researchers are constrained. Meanwhile, the combination of low cost cloud computing, open source software and new methods of data analysis - the enablers of the big data revolution - are transforming research in other fields. Big data research is perfectly possible with legislation if only the basic ingredients - the data, the tools and some tried and trusted methods - were as readily available as the computing power and the storage. The vision for this project is to address that gap by providing a new Legislation Data Research Infrastructure at research.legislation.gov.uk. Specifically tailored to researchers' needs, it will consist of downloadable data, online tools for end-users; and open source tools for researchers to download, adapt and use. There has never been a better time for research into the architecture and content of law. There are three main areas for research: 1.Understanding researchers' needs: to ensure the service is based on evidenced need, capabilities and limitations, putting big data technologies in the hands of non-technical researchers for the first time. 2.Deriving new open data from closed data: No one has all the data that arts and humanities researchers might find useful in a Legislation Data Research Infrastructure. For example, the potentially personally identifiable data about users and usage of legislation.gov.uk cannot be made available as open data but is perfect for processing using big data tools; eg to identify clusters in legislation or "recommendations" datasets of "people who read Act A or B also looked at Act Y or Z". The project will look at whether it is possible to create new open data sets from this type of closed data. An N-Grams dataset and appropriate user interface for legislation or related case law, for example, would contain sequences of words/phrases/statistics about their frequency of occurrence per document. N-Grams are useful for research in linguistics or history, and could also be used to provide a predictive text feature in a drafting tool for legislation. 3.Pattern language for legislation: We need new ways to model the architecture of the statute book if we are to study it using big data. The project will seek to learn from other disciplines, applying the concept of a 'pattern language' to legislation. Pattern languages have revolutionised software engineering over the last twenty years and have the potential to do the same for our understanding of legislation. A pattern language is simply a structured method of describing good design practices, providing a common vocabulary between users and specialists, framed around problems or issues, with a solution. Patterns are not created or invented - they are identified as 'good design' based on evidence about how useful and effective they are. Applied to legislation, this might lead to a common vocabulary between the users of legislation and legislative drafters, to identify more effective drafting practices and design solutions that effect good law. This could also enable a radically different approach to structuring teaching materials or guidance for legislators.