Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/20069
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Workflows for Quantitative Data Analysis in The Social Sciences
Authors: Turner, Kenneth J
Lambert, Paul
Contact Email: kjt@cs.stir.ac.uk
Keywords: e-Social Science
Quantitative Data Analysis
d Scientific Workflow
Service-Oriented Architecture
Statistical Analysis
Issue Date: Jun-2015
Publisher: Springer
Citation: Turner KJ & Lambert P (2015) Workflows for Quantitative Data Analysis in The Social Sciences, International Journal on Software Tools for Technology Transfer, 17 (3), pp. 321-338.
Abstract: The background is given to how statistical analysis is used by quantitative social scientists. Developing statistical analyses requires substantial effort, yet there are important limitations in current practice. This has motivated the authors to create a more systematic and effective methodology with supporting tools. The approach to modelling quantitative data analysis in the social sciences is presented. Analysis scripts are treated abstractly as mathematical functions and concretely as web services. This allows individual scripts to be combined into high-level workflows. A comprehensive set of tools allows workflows to be defined, automatically validated and verified, and automatically implemented. The workflows expose opportunities for parallel execution, can define support for proper fault handling, and can be realised by non-technical users. Services, workflows and datasets can also be readily shared. The approach is illustrated with a realistic case study that analyses occupational position in relation to health.
Type: Journal Article
URI: http://hdl.handle.net/1893/20069
DOI Link: http://dx.doi.org/10.1007/s10009-014-0315-4
Rights: This item has been embargoed for a period. During the embargo 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. Publisher policy allows this work to be made available in this repository; The original publication is available at www.springerlink.com
Affiliation: Computing Science - CSM Dept
Sociology/Social Pol&Criminology

Files in This Item:
File Description SizeFormat 
wf-stats.pdf1.44 MBAdobe PDFView/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 library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.