Computing and Information Systems - Research Publications

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End date: 2009 × Start date: 2000 × Subject: metadata ×

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    Securing interpretability: The case of ega language documentation
    Gibbon, D ; Bow, C ; Bird, S ; Hughes, B (Evaluations and Language resources Distribution Agency, 2004-01-01)
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    Management of metadata in linguistic fieldwork: Experience from the ACLA project
    Hughes, B ; Penton, D ; Bird, S ; Bow, C ; Wigglesworth, G ; McConvell, P ; Simpson, J (European Language Resource Association, 2004-01-01)
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    A resource-oriented data management architecture for nanoCMOS electronics
    Harbulot, B. ; Berry, D. ; Davenhall, C. ; Jones, M. ; Millar, C. ; Roy, G. ; Sinnott, R. ; Stewart, G. ; Asenov, A. (National e-Science Centre, University of Glasgow, 2008)
    The EPSRC pilot project Meeting the Design Challenges of NanoCMOS Electronics (nanoCMOS) began in October 2006 and is focused upon tackling the decreasing scale of modern semiconductor components. This scaling has direct impact upon the complete circuit and system electronics design process due to the variability in transistor behaviour caused by differences in atomic structure. To address these challenges, the project has focused upon large scale device simulations exploiting a wide variety of computational resources. This paper focuses on the approach adopted for managing the many hundreds of thousands of files being generated that are associated with these simulations. Specific challenges in achieving this are related to the fine grained security demanded in protecting intellectual property of data and metadata, and the seamless linkage of metadata associated with services. We believe that this data architecture has widespread applicability to many research areas.
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    Enabling quantitative data analysis through e-infrastructures
    Tan, Koon Leai Larry ; Lambert, Paul S. ; Turner, Ken J. ; Blum, Jesse ; Gayle, Vernon ; Jones, Simon B. ; Sinnott, Richard O. ; Warner, Guy (Sage Publications, 2009)
    This article discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities that are central to quantitative data analysis, referred to as ‘‘data management,’’ can benefit from e-Infrastructural support. We conclude by discussing how these issues are relevant to the Data Management through e-Social Science (DAMES) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences.