Adoption of e-Infrastructure services: configurations of practice.

This paper reports findings from a study of researchers and research-computing support staff. It explores examples of the social relations supporting the adoption, adaptation and domestication of e-Research technologies and e-Infrastructures and makes recommendations for funding organizations, technology suppliers, service providers and institutions.

Adoption and use of Web 2.0 in scholarly communications.

Sharing research resources of different kinds, in new ways, and on an increasing scale, is a central element of the unfolding e-Research vision. Web 2.0 is seen as providing the technical platform to enable these new forms of scholarly communications.

Data integration in eHealth: a domain/disease specific roadmap.

The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects using schizophrenia as a domain-specific test case. It outlines emerging strategies, recommendations and objectives for collaboration on shared ontology-building and harmonization of data for multi-site trials in this domain.

Designing for e-Health: recurring scenarios in developing grid-based medical imaging systems.

The paper draws on a number of Grid projects, particularly on the experience of NeuroGrid, a UK project in the Neurosciences tasked with developing a Grid-based collaborative research environment to support the sharing of digital images and patient data across multiple distributed sites. It outlines recurrent socio-technical issues, highlighting the challenges of scaling up technological networks in advance of the regulatory networks which normally regulate their use in practice.

Working IT out in e-Science: experiences of requirements capture in a HealthGrid project.

This paper reports on our experiences of being involved in requirements capture for a HealthGrid project. Large scale, collaborative projects with multiple partners tend to experience numerous problems in the requirements capture phase (and often beyond) and HealthGrid projects are no exception. Projects with highly innovative objectives often have additional sets of problematics, however.