|Appears in Collections:||Computing Science and Mathematics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Enabling Quantitative Data Analysis through e-Infrastructure|
|Author(s):||Tan, Koon Leai Larry|
Turner, Kenneth J
Blum, Jesse Michael
Social sciences Information services
Information storage and retrieval systems Social sciences Management
Computational grids (Computer systems)
|Citation:||Tan KLL, Lambert P, Turner KJ, Blum JM, Gayle V, Jones S, Sinnott R & Warner G (2009) Enabling Quantitative Data Analysis through e-Infrastructure. Social Science Computer Review, 27 (4), pp. 539-552. https://doi.org/10.1177/0894439309332647.|
|Abstract:||This paper discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities which 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 DAMES (Data Management through e-Social Science) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences.|
|Rights:||The final, definitive version of this article has been published in the Journal, Social Science Computer Review, 27/4, 2009, © SAGE Publications, Inc., 2009 by SAGE Publications, Inc. at the Social Science Computer Review page: http://ssc.sagepub.com/ on SAGE Journals Online: http://online.sagepub.com/|
|Enabling Quantitative Data Analysis.pdf||Fulltext - Accepted Version||452.95 kB||Adobe PDF||View/Open|
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.