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Social Science Computer Review
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What's this?

Enabling Quantitative Data Analysis Through e-Infrastructure

Koon Leai Larry Tan

University of Stirling, klt{at}cs.stir.ac.uk

Paul S. Lambert

University of Stirling, paul.lambert{at}stir.ac.uk

Ken J. Turner

University of Stirling, kjt{at}cs.stir.ac.uk

Jesse Blum

University of Stirling, jmb{at}cs.stir.ac.uk

Vernon Gayle

University of Stirling, vernon.gayle{at}stir.ac.uk

Simon B. Jones

University of Stirling, sbj{at}cs.stir.ac.uk

Richard O. Sinnott

University of Glasgow, r.sinnott{at}nesc.gla.ac.uk

Guy Warner

University of Stirling, gcw{at}cs.stir.ac.uk

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.

Key Words: data management • quantitative data • e-Infrastructure • workflows • metadata

This version was published on November 1, 2009

Social Science Computer Review, Vol. 27, No. 4, 539-552 (2009)
DOI: 10.1177/0894439309332647
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