Statistical analysis and visualization services for spatially integrated social science datasets

Azeezullah, Irfan, Pambudi, Friska, Shyy, Tung-Kai, Azeezullah, Imran, Ward, Nigel, Hunter, Jane and Stimson, Robert J. (2012). Statistical analysis and visualization services for spatially integrated social science datasets. In: E-Science (e-Science), 2012 IEEE 8th International Conference on. IEEE 8th International Conference on E-Science, Chicago Il, United States, (). 08-12 October 2012. doi:10.1109/eScience.2012.6404421

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Author Azeezullah, Irfan
Pambudi, Friska
Shyy, Tung-Kai
Azeezullah, Imran
Ward, Nigel
Hunter, Jane
Stimson, Robert J.
Title of paper Statistical analysis and visualization services for spatially integrated social science datasets
Conference name IEEE 8th International Conference on E-Science
Conference location Chicago Il, United States
Conference dates 08-12 October 2012
Proceedings title E-Science (e-Science), 2012 IEEE 8th International Conference on   Check publisher's open access policy
Journal name 2012 IEEE 8th International Conference on E-Science, e-Science 2012   Check publisher's open access policy
Place of Publication Piscatawa, NJ, United States
Publisher IEEE
Publication Year 2012
Sub-type Fully published paper
DOI 10.1109/eScience.2012.6404421
ISBN 9781467344678
1467344672
9781467344661
1467344664
ISSN 2325-372X
Total pages 8
Collection year 2013
Language eng
Formatted Abstract/Summary
The field of Spatially Integrated Social Science (SISS) recognizes that much data of interest to social scientists has an associated geographic location. SISS systems use geographic location as the basis for integrating heterogeneous social science data sets and for visualizing and analyzing the integrated results through mapping interfaces. However, sourcing data sets, aggregating data captured at different spatial scales, and implementing statistical analysis techniques over the data are highly complex and challenging steps, beyond the capabilities of many social scientists. The aim of the UQ SISS eResearch Facility (SISS-eRF) is to remove this burden from social scientists by providing a Web interface that allows researchers to quickly access relevant Australian socio-spatial datasets (e.g. census data, voting data), aggregate them spatially, conduct statistical modeling on the datasets and visualize spatial distribution patterns and statistical results. This paper describes the technical architecture and components of SISS-eRF and discusses the reasons that underpin the technological choices. It describes some case studies that demonstrate how SISS-eRF is being applied to prove hypotheses that relate particular voting patterns with socio-economic parameters (e.g., gender, age, housing, income, education, employment, religion/culture). Finally we outline our future plans for extending and deploying SISS-eRF across the Australian Social Science Community
Keyword Spatial social science
Data Integration
Statistical analysis
Geospatial information systems
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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