Philip A. Couch

Why Linked Data is Not Enough for Scientists

Scientific data stands to represent a significant portion of the linked open data cloud and science itself stands to benefit from the data fusion capability that this will afford. However, simply publishing linked data into the cloud does not necessarily meet the requirements of reuse. Publishing has requirements of provenance, quality, credit, attribution, methods in order to provide the \emph{reproducibility} that allows validation of results. In this paper we make the case for a scientific data publication model on top of linked data and introduce the notion of \emph{Research Objects} as first class citizens for sharing and publishing.

IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy

BACKGROUND Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills. OBJECTIVES To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers. METHODS The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data. RESULTS The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data. CONCLUSIONS We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.

Molecular dynamics in a grid computing environment: experiences using DL_POLY_3 within the eMinerals escience project

We use the example of a study of the compressibility anomaly in amorphous silica to illustrate how molecular-scale simulations can be performed using grid computing. The potential for running many simulations within a single study requires the use of new data management methods, which are discussed in this paper. The example of silica highlights the advantages of the use of grid computing for studying subtle effects.

IMPACT: A generalisable system for simulating public health interventions.

Populations are under-served by local health policies and management of resources, partly because of a lack of realistically complex models to enable a wide range of potential options to be appraised. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners because they do not have the requisite technical knowledge or skills. This paper presents a system for creating, executing and analyzing the results of simulated public health and healthcare policy interventions, which is more accessible and usable by modellers and policy-makers alike.

Information Delivery in Computational Mineral Science: The eMinerals Data Handling System

Escience technologies are designed to address problems arising in the practice of computational science. The outcome of computational science is the generation of data, and a significant portion of these problems concern Information Delivery: the process of disseminating data across virtual organizations, and of contextualizing that data so that relevant quantities may be extracted and examined with the minimum of difficulty. This paper describes some of these issues encountered in the particular field of computational mineral science, and the solutions that the eMinerals consortium has developed to address them.

E-Labs and the stock of health method for simulating health policies

Regional outcomes of national health policies are difficult to forecast. This is partly due to a lack of realistically complex models that can be used to appraise policy options and partly a lack of accessible and adaptable tools that can be used to simulate the consequences of policy decisions. These barriers might be overcome by exploiting the commoditization of massively parallel computing architectures, advances in machine learning, and the increased availability of large-scale linked healthcare data. This paper presents a novel modelling methodology, The Stock of Health, for harnessing emerging data and computational resources to simulate health policy, with application initially to coronary heart disease. We detail the use of multi-core graphical processing architectures to facilitate a micro-simulation approach. The simulation tools have been deployed through the IMPACT Framework. We explore how this framework can be extended to support the sharing and reuse of policy models and simulations based on the digital publishing concept of e-Lab.

Sharable simulations of public health for evidence based policy making

Local health policies are not as evidence based as they could be if the public health impacts of policies were easier to simulate. Here we address the inaccessibility of high quality models of public health and policy — presenting the concepts of a new simulation framework, IMPACT, built on Semantic Web principles. Model and simulation data are persisted with rich semantics and context to support sharing and interpretation. For this purpose, graph storage systems are explored alongside a new framework for mapping clinical data objects to graphical models. The computation employs functional programming for the parallelised simulation of locally representative populations/cohorts changing over time. The input data, model information and simulation results are mapped to social networks of policy making using the Work/Research Object and e-Lab paradigm that is emerging in E-Science.

Computational Grids for Mid-Sized Collaborative Projects: The eMinerals Experience

Grid computing has the potential to revolutionise how small groups of simulation scientists work together to tackle new science problems. In this paper we report how the eMinerals project has developed a small scale integrated compute and data grid infrastructure - the eMinerals minigrid - and developed generic job submission tools that exploit this infrastructure and which enable the science users to also access other grid systems.

Developing and validating a novel questionnaire to capture bio-psycho-social variables of allergic reactions in the community: the AlleRiC study and the preliminary analyses

Allergic disease is a growing health risk in the modern world, while its management at professional and patients’ levels is unsatisfactory. There is no register of prevalence and biopsychosocial co-factors of allergic reactions as they occur in real world settings. The Allergic Reactions in the Community (AlleRiC) study aims to develop and validate an on-line questionnaire to allow real time food allergic reactions to be reported, with scope for an in depth exploration of related real-world factors. Methods Following focus groups and an expert evaluation, an item pool of 81 items was generated. 39 adults from Ireland and UK, diagnosed with food allergy, evaluated a prototype of the AlleRiC online questionnaire. Individual items of the prototype were psychometrically assessed via a novel Evaluative Scale measuring five different facets of the questions. Results Individual items were evaluated positively by participants (60-70% of positive scores on the Evaluative Scale). Preliminary psychometric analyses of the questionnaire’s items showed good construct, convergent and face validity (Cronbach’s Alpha >0.7). With reference to co-factors, reactions occurred most often in a social context (67% of cases), especially in small groups (29% of cases) of family members, relatives and close friends (44% of cases). 77% of companions were aware of the participants’ food allergy diagnosis. Reactions had a psychological impact with 87% of cases indicating a change in emotional affect following a reaction (from positive to negative affect). Conclusions The AlleRiC study demonstrates potential to provide novel findings, which may give new understanding of the real-world, real time factors t hat give rise to, or prevent, reactions. Such findings will have implications for food allergy management across Europe. As a new psychometric tool: the AlleRiC questionnaire is now undergoing further validation.

OP71 Comparing coronary mortality reductions by shifting the population blood pressure distribution versus improved management of hypertensive patients: modelling study

Background Blood pressure reduction is an important target for the prevention of coronary heart disease (CHD). In 1982, Rose proposed that small population-wide reductions in blood pressure, through public health measures to reduce salt intake, might deliver larger reductions in CHD mortality than by treating hypertensive patients. We aimed to estimate the potential for each strategy to reduce future CHD deaths in England and Wales. Methods We used the Stock of Health (SoH) model, where each individual is born with a 100% stock which then depreciates year-by-year, reflecting fixed and modifiable risk factors. A CHD death occurs when the individual’s CHD’s SoH falls below a critical point. Births, deaths and risk factor distributions were obtained from the Office of National Statistics and the Health Survey for England. Model parameters were calibrated using data from the US Cardiovascular Lifetime Risk Pooling Project. We modelled ten policy scenarios: population-wide, individual-based and combination strategies. The population-wide strategies were: a systolic blood pressure (SBP) reduction of 0.1 mmHg achieved by health promotion media strategies (Pop1), a 1.3 mmHg reduction achieved by mandatory salt reformulation (Pop2) and an attainable goal where SBP levels fall to those observed in the US population (Pop3). The individual-based strategies assumed that in currently uncontrolled hypertensive patients, control was then achieved in 30% (Indi1) and 50% (Indi2) of them. Results We forecast that approximately 467,200 CHD (95% CI 466,900–467,600) deaths may occur between 2013 and 2030. By controlling 30% and 50% of hypertensive patients, we predict approximately 3800 (3200–4300) and 6200 (5700–6800) fewer deaths respectively. Conversely, we predict approximately 1300 (800–1900) fewer deaths by health promotion; some 16,400 (15,800–16,900) fewer deaths by mandatory reformulation and approximately 25,400 (24,900–25,900) fewer deaths by gradual SBP declines to US levels. Combining Pop1 and Indi1 might achieve approximately 5100 (4500–5600) fewer deaths in 2030; whereas combining Pop1 and Indi2 could achieve some 7500 (2000–13,000) fewer deaths. Combining Pop2 and Indi1 might prevent approximately 19,700 (19,200–20,300) deaths; while combining Pop2 and Indi2 could prevent or postpone some 21,900 (21,400–22,400) deaths by 2030. Conclusion Both population-wide salt reduction policies and individual-based treatment strategies could substantially reduce CHD deaths in England and Wales. Even greater reductions in mortality might be achieved by reducing SBP to US levels. However, there is no clear single successful intervention, but both types of strategies are needed to maximise our chances of controlling the burden of mortality attributable to blood pressure.