This paper describes a group of online services which are designed to support social survey research and the production of statistical results. The 'Grid Enabled Specialist Data Environment' (GESDE) services constitute three related systems which offer facilities to search for, extract and exploit supplementary data and metadata concerned with the measurement and operationalisation of survey variables. The services also offer users the opportunity to deposit and distribute their own supplementary data resources for the benefit of dissemination and replication of the details of their own analysis. The GESDE services focus upon three application areas: specialist data relating to the measurement of occupations; educational qualifications; and ethnicity (including nationality, language, religion, national identity). They identify information resources related to the operationalisation of variables which seek to measure each of these concepts - examples include coding frames, crosswalk and translation files, and standardisation and harmonisation recommendations. These resources constitute important supplementary data which can be usefully exploited in the analysis of survey data. The GESDE services work by collecting together as much of this supplementary data as possible, and making it searchable and retrievable to others. This paper discusses the current features of the GESDE services (which have been designed as part of a wider programme of ‘e-Science’ research in the UK), and considers ongoing challenges in providing effective support for variable-oriented statistical analysis in the social sciences.

The Economic and Social Research Council (ESRC)-funded Data Management through e-Social Sciences (DAMES) project is investigating, as one of its four research themes, how research into depression, self-harm and suicide may be enhanced through the adoption of e-Science infrastructures and techniques. In this paper, we explore the challenges in supporting such research infrastructures and describe the distributed and heterogeneous datasets that need to be provisioned to support such research. We describe and demonstrate the application of an advanced user and security-driven infrastructure that has been developed specifically to meet these challenges in an on-going study into depression, self-harm and suicide.

The JISC-funded National e-Infrastructure for Social Simulation (NeISS) project aims to develop and provide new services to social scientists and public/private sector policymakers interested in “what-if” questions that have an impact upon society and can be tackled through social simulation. For the first what-if question, a traffic simulation modelling how congestion will affect routes within a city or region projected across a time-span of decades has been identified. This paper describes the work that has been done in implementing a secure, user-oriented environment that provides seamless access to relevant nationally significant data sets such as the 2001 Census and demographic transition statistics from the British Household Panel Survey (BHPS) , and a Population Reconstruction Model (PRM) simulator, which simulates a population of individuals or households based upon these data sets.

Deposited with permission of the authors. © 2009 R. O. Sinnott, T. Doherty, J. Jiang, S. McCafferty, A. Stell & J.Watt

As the proliferation of digital data about individuals increases the opportunities for leveraging this information to benefit society become correspondingly greater. This is especially true in the domain of e-Health where a large number of disparate clinical data resources exist around the world, often housed in individual systems, but with great potential to advance medical and health-care provision if harnessed together and linked with other data resources. In this paper we present a variety of projects that federate such health and other data through re-usable and adaptable e-Infrastructures targeted to the needs of the Scottish and wider e-Research communities. At the heart of all these systems and to counter societies natural wariness of such systems and their use of their personal information are fine grained and adaptable security systems which restrict and enforce access to data to authorised individuals. In this paper we outline these e-Infrastructure architectures, their associated security models and how we are applying them to support epidemiological studies.

How many people have had a chronic disease for longer than 5-years in Scotland? How has this impacted upon their employment? Are there any geographical clusters in Scotland where a high-incidence of patients with such long-term illness can be found? How does the life expectancy of such individuals compare with the national averages? Such questions are important to understand the health of nations and the best ways in which health care should be delivered and measured for their impact and success. In tackling such research questions, e-Infrastructures need to provide tailored, secure access to an extensible range of distributed resources including, amongst others, primary and secondary e-Health clinical data; social science data; and geospatial data. In this paper we describe the security models underlying these e-Infrastructures and demonstrate their implementation in supporting secure, federated access to a variety of distributed and heterogeneous data sets, exploiting the results of a variety of projects at the National e-Science Centre (NeSC) at the University of Glasgow. 1. Introduction Much scientific research now crosses the boundaries of individual research disciplines. For example, if one considers studies in particular chronic diseases and the response of specialised study-specific treatments then this can require interplay between the clinical sciences, the biological sciences, the social sciences and the geospatial sciences amongst others. To accommodate such inter-disciplinary research, e-Research infrastructures seek to support the seamless and transparent linkage across disciplines and the resources they offer. Furthermore, this has to be aligned with the way in which the researchers themselves wish to work, and satisfy all concerns associated with the numerous stakeholders in this space, e.g. on security, access control and individual privacy. This is made especially challenging given the evolving nature of science and the associated resources available, and the often dynamic nature of collaborations themselves. Some research applications are primarily computationally-bound, whereby access to large high performance computing (HPC) facilities is the primary handicap restricting scientific progress. Resources such as the UK e-Science National Grid Service (www.ngs.ac.uk) and ScotGrid (www.scotgrid.ac.uk) can provide this capacity. However, these resources are still largely established for the computationally proficient, who are able to deal with the nuances and intricacies of complex Grid middleware. Indeed the initial step in gaining access to such

This is a pre-print of a paper from UK e-Science All Hands Meeting 2008. http://www.allhands.org.uk/2008/index.html