Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/2986
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A Social Science Data Fusion Tool and the Data Management through e-Social Science (DAMES) Infrastructure
Authors: Warner, Guy
Blum, Jesse Michael
Jones, Simon
Lambert, Paul
Turner, Kenneth J
Tan, Koon Leai Larry
Dawson, Alison
Bell, David
Contact Email: sbj@cs.stir.ac.uk
Keywords: Social Science
Data Management
Infrastructure
Grid Technologies
e-Science
Issue Date: 28-Aug-2010
Publisher: Royal Society
Citation: Warner G, Blum JM, Jones S, Lambert P, Turner KJ, Tan KLL, Dawson A & Bell D (2010) A Social Science Data Fusion Tool and the Data Management through e-Social Science (DAMES) Infrastructure, Philosophical Transactions of the Royal Society. A: Mathematical and Physical Sciences, 368 (1925), pp. 3859-3873.
Abstract: The last two decades have seen substantially increased potential for quantitative social science research. This has been made possible by the significant expansion of publicly available social science datasets, the development of new analysis methodologies such as microsimulation, and increase in computing power. These rich resources do, however, bring with them substantial challenges associated with organising and using data. These processes are often referred to as 'data management'. The DAMES project (Data Management through e-Social Science) is working to support activities of data management for social science research. This paper describes the DAMES infrastructure, focusing on the data fusion process that is central to the project approach.
Type: Journal Article
URI: http://hdl.handle.net/1893/2986
DOI Link: http://dx.doi.org/10.1098/rsta.2010.0159
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author; you can only request a copy if you wish to use this work for your own research or private study.
Affiliation: Computing Science - CSM Dept
Computing Science and Mathematics
Computing Science - CSM Dept
Sociology/Social Pol&Criminology
Computing Science - CSM Dept
University of Stirling
Applied Social Science
Economics

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