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The research catalogue is an archive of ESRC-funded grants and outputs. Links, files and other content will no longer be maintained or updated after April 2014.

E-Social Science Centre Lancaster Node

The overall aim of this joint project between Lancaster University and CCLRC Daresbury is to ensure the effective development and use of GRID-enabled quantitative methods. As well as undertaking research and development of e-research tools, CQeSS will provide awareness raising, training and support in e-research for quantitative Social Scientists. CQeSS is a node of the National Centre for e-Social Science (NCeSS).

CQeSS aims are:

  • 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.

To achieve these aims CQeSS will undertake the following activities:

  • Contribute to the reviews of the potential/possibilities for Grid-enabled quantitative methods for substantive grand challenges, as well as assess the appropriateness of existing training and support activities;
  • Help to provide appropriate middleware and middleware training for quantitative e-Social Science research;
  • Help to provide an awareness-raising and quantitative e-Social Science training programme that involves a dialogue between computer/computational scientists and those researchers involved in substantive research, methodology and data base management;
  • Construct a Portal integrating awareness-raising, training, and support in quantitative methods for e-Social Science;
  • Provide research exemplars that illustrate the use and potential of quantitative e-Social Science.
  • Outputs (103)