Authentication and authorization for Grids is a challenging security issue. In this paper, key issues for the establishment of Grid authentication and authorization infrastructures are discussed, and an overview of major Grid authentication and authorization technologies is presented. Related to this, recent developments in Grid authentication and authorization infrastructures suggest adoption of the Shibboleth technology which offers advantages in terms of usability, confidentiality, scalability and manageability. When combined with advanced authorization technologies, Shibboleth-based authentication and authorization infrastructures provide role-based, fine-grained authorization. We share our experience in constructing a Shibboleth-based authentication and authorization infrastructure and believe that such infrastructure provides a promising solution for the security of many application domains.

This paper aims to illustrate the potential benefits for academic end-users of integrating existing efforts around describing, building, and using Grid infrastructures. It shows that UK e-Science and e-Social Science projects, among others, can be documented with different levels of user abstraction to facilitate understanding and sharing of the expertise acquired when using Grids and developing Grid-based e-Science and e-Social Science applications. The research study presented uses three existing service-oriented approaches to test the viability of capturing and abstracting the Grid services used in a particular project, and thereby, going beyond document-centric approaches. Each of the three approaches exhibits different levels of abstraction and formalisation and is illustrated by a Grid-based application from the Social Sciences. This example is used to underpin the proposal that it is time to move towards the creation of a collective Knowledge Base that goes beyond presenting projects solely in the scientific literature.

This article discusses the use of Grid technology to integrate the data, computation and presentation elements of an empirical economic modelling process. We achieve this by using a form of statistical data fusion developed in the poverty mapping literature to address a substantive issue: determining United Kingdom ethnic minority welfare. Elements of this methodology appear to be well suited to such grid-enablement, and we present and illustrate our implementation using the context of this microdata application.

This article presents and discusses the motivation, methodology and implementation of an e-Social Science pilot demonstrator project entitled: Grid Enabled Micro-econometric Data Analysis (GEMEDA). This used the National Grid Service (NGS) to investigate a policy relevant Social Science issue: the welfare of ethnic minority groups in the United Kingdom. The underlying problem is that of a statistical analysis that uses quantitative data from more than one source. The application of grid technology to this problem allows one to integrate elements of the required empirical modelling process: data extraction, data transfer, statistical computation and results presentation, in a manner that is transparent to a casual user.

A key reason for e-Science and e-Social Science applications to embrace a services-oriented approach is to participate in the sharing of standards, thus simplifying modifications or extensions of current applications as well as facilitating the engineering of new ones with a substantial reduction in the amount of code needed. Reducing the amount of code replicated within and across e-Science and e-Social Science applications will have an impact into code creation and code maintenance and save time and money. This paper uses the experience of the eIUS project and reflects upon methodologies that would facilitate technical interoperability within and across education and research in a way that minimises the effort required for developers and academic end-users.

The aim of the ConvertGrid project was to demonstrate the advantages that Grid technologies can bring to the social sciences, by using such technologies to address key problems facing researchers who want to combine data from multiple geo-referenced data sets. The ConvertGrid project has developed a Grid based solution to this problem of geographical conversion. The ConvertGrid system has expanded upon the capabilities of the existing Convert service by linking it to potential data resources via the Grid. It enables users to select data of interest across a range of topics from multiple datasets, convert this data to a common target geography using geographical conversion tables. The resultant data streams are combined and returned to the user or transferred automatically to a web based mapping/visualisation interface. All the data retrieval and geographical conversion processes are hidden from the user. The ConvertGrid project has demonstrated how Grid technologies can be used to automate very complex workflows and also help to stimulate novel forms of research through promoting increased and more effective use of multiple data sources. However, developing a Grid based service to access, integrate and analyse multiple datasets which is simple to use has required the project team to address a number of key technical and/or methodological challenges. 1. Background The ConvertGrid project was funded as part of the ESRC Pilot Projects in e-Social Science Programme. The overall aim of the ConvertGrid project was to demonstrate the advantages that Grid technologies can bring to the social sciences (Cole, Schurer, Beedham and Hewitt 2003), by using such technologies to address two common problems facing researchers who want to combine data from multiple geo-referenced data sets. The problems in question are: • the initial data management problem of geography conversion, and • the subsequent data fusion problem of combining the converted data.