Computing and Information Systems - Research Publications
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ItemGrid security(CRC Press, 2009)Security is essential for inter-organizational collaborative e-Research. Without robust, reliable, easy to understand and manage e-Research security models and their implementations many communities and wider industry will simply not engage. To support inter-organizational, inter-disciplinary research it is essential e-Research security infrastructures support several key (defining) characteristics …
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ItemMulti-level simulations to support nanoCMOS electronics research(International Design Engineering Technical Conferences & Computers and Information in Engineering, 2009)
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ItemSecurity-oriented portals for the life sciences(Oxford University Press, 2009)Motivation: The life sciences are broad in scope and cover multi- and inter-disciplinary domains as well as the biological domain. These domains can for example involve researchers from the clinical, social, geo-spatial and computer sciences amongst others, e.g. in understanding genetic variations across a population as might be undertaken through a genome-wide association study. Given, this it is essential that portals for these communities are targeted to the individual expertise of the particular domain scientists. Thus tools available to a bioinformatician through a portal might well be meaningless to a social scientist and vice versa. Furthermore certain domains demand that fine-grained access control on data is supported. In this paper we outline how a portfolio of life science related projects at the National e-Science Centre (NeSC) at the University of Glasgow have benefited from security-oriented portals focused upon ease of access, configuration and usage, where data providers are assumed to be autonomous and able to make their own local fine-grained access control decisions. We describe the basic technologies that underlie these solutions and outline specific case studies in their application in the areas of depression, self-harm and suicide, and in the area of paediatric endocrinology focusing in particular on rare diseases associated with sex development.
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ItemE-infrastructures fostering multi-centre collaborative research into the intensive care management of patients with brain injury(Information Science Reference (an imprint of IGI Global), 2009)Clinical research is becoming ever more collaborative with multi-centre trials now a common practice. With this in mind, never has it been more important to have secure access to data and, in so doing, tackle the challenges of inter-organisational data access and usage. This is especially the case for research conducted within the brain injury domain due to the complicated multi-trauma nature of the disease with its associated complex collation of time-series data of varying resolution and quality. It is now widely accepted that advances in treatment within this group of patients will only be delivered if the technical infrastructures underpinning the collection and validation of multi-centre research data for clinical trials is improved. In recognition of this need, IT-based multi-centre e-Infrastructures such as the Brain Monitoring with Information Technology group (BrainIT - www.brainit.org) and Cooperative Study on Brain Injury Depolarisations (COSBID - www.cosbid.de) have been formed. A serious impediment to the effective implementation of these networks is access to the know-how and experience needed to install, deploy and manage security-oriented middleware systems that provide secure access to distributed hospital based datasets and especially the linkage of these data sets across sites. The recently funded EU framework VII ICT project Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AVERT-IT) is focused upon tackling these challenges. This chapter describes the problems inherent to data collection within the brain injury medical domain, the current IT-based solutions designed to address these problems and how they perform in practice. The authors outline how the authors have collaborated towards developing Grid solutions to address the major technical issues. Towards this end we describe a prototype solution which ultimately formed the basis for the AVERT-IT project. They describe the design of the underlying Grid infrastructure for AVERT-IT and how it will be used to produce novel approaches to data collection, data validation and clinical trial design.
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ItemTool Support for Security-oriented Virtual Research Collaborations(IEEE COMPUTER SOC, 2009)
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ItemA clinical grid infrastructure supporting adverse hypotensive event prediction(IEEE Computer Society, 2009)The condition of hypotension - where a person's arterial blood pressure drops to an abnormally low level - is a common and potentially fatal occurrence in patients under intensive care. As medical interventions to treat such events are typically reactive and often aggressive, there would be great benefit in having a prediction system that can warn health-care professionals of an impending event and thereby allow them to provide non-invasive, preventative treatments. This paper describes the progress of the EU FP7 funded Avert-IT project, which is developing just such a system using Bayesian neural network learning technology based upon an integrated, real-time data grid infrastructure, which draws together heterogeneous data-sets from six clinical centres across Europe.
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ItemDesigning privacy for scalable electronic healthcare linkage(IEEE Computer Society, 2009)A unified electronic health record (EHR) has potentially immeasurable benefits to society, and the current healthcare industry drive to create a single EHR reflects this. However, adoption is slow due to two major factors: the disparate nature of data and storage facilities of current healthcare systems and the security ramifications of accessing and using that data and concerns about potential misuse of that data. To attempt to address these issues this paper presents the VANGUARD (Virtual ANonymisation Grid for Unified Access of Remote Data) system which supports adaptive security-oriented linkage of disparate clinical data-sets to support a variety of virtual EHRs avoiding the need for a single schematic standard and natural concerns of data owners and other stakeholders on data access and usage. VANGUARD has been designed explicit with security in mind and supports clear delineation of roles for data linkage and usage.
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ItemData privacy by design: digital infrastructures for clinical collaborations(International Society for Research in Science and Technology, 2009)The clinical sciences have arguably the most stringent security demands on the adoption and roll-out of collaborative e-Infrastructure solutions such as those based upon Grid-based middleware. Experiences from the Medical Research Council (MRC) funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project and numerous other real world security driven projects at the UK e-Science National e-Science Centre (NeSC – www.nesc.ac.uk) have shown that whilst advanced Grid security and middleware solutions now offer capabilities to address many of the distributed data and security challenges in the clinical domain, the real clinical world as typified by organizations such as the National Health Service (NHS) in the UK are extremely wary of adoption of such technologies: firewalls; ethics; information governance, software validation, and the actual realities of existing infrastructures need to be considered from the outset. Based on these experiences we present a novel data linkage and anonymisation infrastructure that has been developed with close co-operation of the various stakeholders in the clinical domain (including the NHS) that addresses their concerns and satisfies the needs of the academic clinical research community. We demonstrate the implementation of this infrastructure through a representative clinical study on chronic diseases in Scotland.
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ItemThe brain monitoring with information technology (BrainIT) collaborative network: EC feasibility study results(Springer, 2009)BACKGROUND: The BrainIT group works collaboratively on developing standards for collection and analyses of data from brain injured patients towards providing a more efficient infrastructure for assessing new health care technology. EC funding supported meetings over a year to discuss and define a core dataset to be collected with IT based methods from patients with traumatic brain injury. We now report on the results of a follow-up period of funding to test the feasibility for collection of the core dataset with IT based methods. METHODS: Over a three year period, data collection client and web-server based tools were developed and core data (grouped into 9 categories) were collected from 200 head-injured patients by local nursing staff. Data were uploaded by the BrainIT web and random samples of received data were selected automatically by computer for validation by data validation (DV) research nurse staff against gold standard sources held in the local centre. Validated data were compared with original data sent and percentage error rates calculated by data category. Feasibility was assessed in terms of the amount of missing data, accuracy of data collected and limitations reported by users of the IT methods. FINDINGS: Thirteen percent of data files required cleaning. Thirty “one-off” demographic and clinical data elements had significant amounts of missing data (> 15%). Validation nurses conducted 19,461 comparisons between uploaded database data with local data sources and error rates were generally less than or equal to 6%, the exception being the surgery data class where an unacceptably high error rate was found. Nearly 10,000 therapies were successfully recorded with start-times but approximately a third had inaccurate or missing end times which limits analyses assessing duration of therapy. Over 40,000 events and procedures were recorded but events with long durations (such as transfers) were more likely to have “end-times” missed. CONCLUSIONS: The BrainIT core dataset is a rich dataset for hypothesis generation and post-hoc analyses provided studies avoid known limitations in the dataset. Limitations in the current IT based data collection tools have been identified and have been addressed. Future academic led multi-centre data collection projects must decrease validation costs and likely will require more direct electronic access to hospital based clinical data sources for both validation purposes and for reducing the research nurse time needed for double data entry. This type of infrastructure will foster remote monitoring of patient management and protocol adherence in future trials of patient management and monitoring.
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