Collaboration for Quantitative e-Social Science (CQeSS)
Project Overview
Based at the Centre for e-Science at the University of Lancaster and CCLRC Daresbury, the Colaboratory for Quantitative e-Social Science (CQeSS) is the NCeSS research node for developing and supporting Quantitative e-Social Science. The node is currently funded from September 2004 to August 2007.
- The further development and deployment of Lancaster’s Statistical Analysis of Binary Recurrent Events (SABRE) software.
- The further development and application of Grid Resources On Workstations Library middleware. GROWL is a lightweight toolkit aimed at providing user friendly Grid access to (heritage) applications via a client-server architecture using web services. The use of GROWL is being demonstrated with Grid enabled SABRE.
- The development and provision of a portal interface to provide access to Grid enabled resources and software on the National Grid Service and the North West Grid. The portal solution will encourage Grid uptake by non specialists and aid collaborative working between a community of scientists engaged in similar research. For this purpose we are developing or deploying a range tools to in the SAKAI portal framework, for more information go to our VRE website
- In cooperation with our ReDReSS project, we are providing a growing resource (training, awareness raising and background material) of relevance to exploiting e-Social Science technology in the social sciences. The material includes presentations from workshops and the NCeSS winter training school and other topical events organised as part of the ReDReSS/CQeSS programme.
With the above activities we aim to achieve the following goals:
- To become an internationally recognized Centre for Quantitative e-Social Science
- To help stimulate the uptake of quantitative e-Social Science methodologies and technologies in the social sciences, government agencies, social and health services, industry and commerce
- To develop e-Science tools appropriate to quantitative e-Social Science
- To create a virtual community of quantitative e-Social Scientists
- To provide some of the appropriate stepping stones and training in quantitative e-Science for social scientists
- To contribute to, and benefit from, the core e-Science programme, the ESRC e-Social Science programme and the activities of NCeSS
Progress
10/6/2009 - SABRE6 is now running in parallel on the DL1 cluster and has been tested with several of the benchmark cases.
Publications
R. Crouchley, R.J. Allan Longitudinal Statistical Modelling on the Grid, in SAGE Handbook of Online Research Methods, eds. N. Fielding, R.M. Lee and G. Blank (SAGE, 2008) pp.471-490
D. Grose, R. Crouchley, T. van Ark, J. Kewley, R.J. Allan, A.L. Braimah, et al. sabreR: Grid-enabling the analysis of multi-process random effect response data in R, Proc. Second International Conference on e-Social Science, Second International Conference on e-Social Science (2006)
D. Grose High Throughput Distributed Computing using R: the multiR Package Journal of Statistical Software (2009, in press)