Abstract

Abstract
This paper describes the present state of evolution of the "Brain Imaging Network Grid" (BING) project in Portugal. This network is composed of 5 nodes connected through a Gbps dark fiber bitways and is served by two clusters and (-)60 TBytes of storage. A distributed information system to support operations and manage the BING community is already in place and further developments to evolve the infrastructure to provide computational neurosciences services are under way and described in the present paper. Moreover, we undercover the architecture that we are implementing that includes the intention to add BING resources to the EGEE node IEETA/UA has been exploring since 2005 under the EGEE Biomed VO. Other aspects of the BING infrastructure evolution aimed to constitute a Grid virtual community in brain imaging are presented and discussed.

Abstract
Digital medical imaging poses challenging requirements to computer science, calling for methods able to efficiently address large data sets and complex processing. Production Grid infrastructures are available, ready to provide on-demand scalable processing power and robust storage. These infrastructures, however, still expose many technical complexities to end-users and domain application developers. In this context, the ability to access Grid services in a seamless, user-friendly way is paramount to bring the Grid potential to clinical users and biomedical researchers. In this paper, we present a Grid-interfacing portal, aiming at raising the level of usability of the Grid to medical research users. In the MAGI portal, the researcher works with domain semantics, including concepts like subject, study and dataset, while the Grid operations, specially storage, are transparently supported by a services framework we have developed. The framework provides high-level, application-developer friendly services to interface the gLite middleware. The portal was also designed to support intuitive, visual interactions, like drag-and-drop, to execute the main use cases.

Abstract

Abstract
The present paper introduces the GERES-nned project and proposes a Grid architecture to cope with its demanding requirements. GERES-med aims at developing a Grid-enabled repository of multimedia information relevant for medical applications, education and research, focussing the cardiology and gastroenterology areas. The overall goal of the project is to make available large volumes of already existing clinical information locked in Clinical Centers through a semantic aware layer providing high-quality classified cases. GERES-med will integrate and develop tools for automated generation of semantic descriptors to support content-based retrieval on the Grid-enabled repository. As a higher level goal, we will try to define a next generation standards-based platform for these medical and academic communities to access, share and discover clinical data, with emphasis on medical images and clinical reports. This paper is a technical contribution describing the GERES-med requirements and proposes a computing architecture to address the identified scenarios.

Abstract