@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 = {http://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
}

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