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.
Description
Enabling Quantitative Data Analysis Through e-Infrastructure
%0 Journal Article
%1 Tan01112009
%A Tan, Koon Leai Larry
%A Lambert, Paul S.
%A Turner, Ken J.
%A Blum, Jesse
%A Gayle, Vernon
%A Jones, Simon B.
%A Sinnott, Richard O.
%A Warner, Guy
%D 2009
%J Social Science Computer Review
%K DDIbibliography
%N 4
%P 539-552
%R 10.1177/0894439309332647
%T Enabling Quantitative Data Analysis Through e-Infrastructure
%U http://ssc.sagepub.com/content/27/4/539.abstract
%V 27
%X 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.
@article{Tan01112009,
abstract = {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.},
added-at = {2016-02-18T09:57:58.000+0100},
author = {Tan, Koon Leai Larry and Lambert, Paul S. and Turner, Ken J. and Blum, Jesse and Gayle, Vernon and Jones, Simon B. and Sinnott, Richard O. and Warner, Guy},
biburl = {https://www.bibsonomy.org/bibtex/24b710fe5336d4ef8385084f1e08a7b1e/knutwenzig},
description = {Enabling Quantitative Data Analysis Through e-Infrastructure},
doi = {10.1177/0894439309332647},
eprint = {http://ssc.sagepub.com/content/27/4/539.full.pdf+html},
interhash = {c8f10f740e51c9b353d4eee3840072fc},
intrahash = {4b710fe5336d4ef8385084f1e08a7b1e},
journal = {Social Science Computer Review},
keywords = {DDIbibliography},
number = 4,
pages = {539-552},
timestamp = {2016-02-18T09:57:58.000+0100},
title = {Enabling Quantitative Data Analysis Through e-Infrastructure},
url = {http://ssc.sagepub.com/content/27/4/539.abstract},
volume = 27,
year = 2009
}