1,788 research outputs found

    Security and confidentiality approach for the Clinical E-Science Framework (CLEF)

    Get PDF
    Objectives: CLEF is an MRC sponsored project in the E-Science programme that aims to establish methodologies and a technical infrastructure for the next generation of integrated clinical and bioscience research. Methods: The heart of the CLEF approach to this challenge is to design and develop a pseudonymised repository of histories of cancer patients that can be accessed by researchers. Robust mechanisms and policies have been developed to ensure that patient privacy and confidentiality are preserved while delivering a repository of such medically rich information for the purposes of scientific research. Results: This paper summarises the overall approach adopted by CLEF to meet data protection requirements, including the data flows, pseudonymisation measures and additional monitoring policies that are currently being developed. Conclusion: Once evaluated, it is hoped that the CLEF approach can serve as a model for other distributed electronic health record repositories to be accessed for research

    Security and confidentiality approach for the Clinical E-Science Framework (CLEF)

    Get PDF
    CLEF is an MRC sponsored project in the E-Science programme that aims to establish policies and infrastructure for the next generation of integrated clinical and bioscience research. One of the major goals of the project is to provide a pseudonymised repository of histories of cancer patients that can be accessed by researchers. Robust mechanisms and policies are needed to ensure that patient privacy and confidentiality are preserved while delivering a repository of such medically rich information for the purposes of scientific research. This paper summarises the overall approach adopted by CLEF to meet data protection requirements, including the data flows and pseudonymisation mechanisms that are currently being developed. Intended constraints and monitoring policies that will apply to research interrogation of the repository are also outlined. Once evaluated, it is hoped that the CLEF approach can serve as a model for other distributed electronic health record repositories to be accessed for research

    Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images

    Full text link
    The quality of modern astronomical data, the power of modern computers and the agility of current image-processing software enable the creation of high-quality images in a purely digital form. The combination of these technological advancements has created a new ability to make color astronomical images. And in many ways it has led to a new philosophy towards how to create them. A practical guide is presented on how to generate astronomical images from research data with powerful image-processing programs. These programs use a layering metaphor that allows for an unlimited number of astronomical datasets to be combined in any desired color scheme, creating an immense parameter space to be explored using an iterative approach. Several examples of image creation are presented. A philosophy is also presented on how to use color and composition to create images that simultaneously highlight scientific detail and are aesthetically appealing. This philosophy is necessary because most datasets do not correspond to the wavelength range of sensitivity of the human eye. The use of visual grammar, defined as the elements which affect the interpretation of an image, can maximize the richness and detail in an image while maintaining scientific accuracy. By properly using visual grammar, one can imply qualities that a two-dimensional image intrinsically cannot show, such as depth, motion and energy. In addition, composition can be used to engage viewers and keep them interested for a longer period of time. The use of these techniques can result in a striking image that will effectively convey the science within the image, to scientists and to the public.Comment: 104 pages, 38 figures, submitted to A
    • …
    corecore