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 |
Author(s): | 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 |
Date Deposited: | 6-May-2014 |
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. https://doi.org/10.1007/s10009-014-0315-4 |
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. |
DOI Link: | 10.1007/s10009-014-0315-4 |
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Files in This Item:
File | Description | Size | Format | |
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wf-stats.pdf | Fulltext - Accepted Version | 1.44 MB | Adobe PDF | View/Open |
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