A Grid Paradigm for e-Science Applications

A Grid Paradigm for e-Science Applications

Livia Torterolo (University of Genoa, Italy), Luca Corradi (University of Genoa, Italy), Barbara Canesi (University of Genoa, Italy), Marco Fato (University of Genoa, Italy), Roberto Barbera (University of Catania and INFN Catania, Italy), Salvatore Scifo (Consorzio Cometa of Catania, Italy) and Antonio Calanducci (INFN-Catania, Italy)
DOI: 10.4018/978-1-60566-374-6.ch031
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This chapter describes a Grid oriented platform -the Bio Med Portal- as a new tool to promote collaboration and cooperation among scientists and healthcare research groups, enabling the remote use of resources integrated in complex software platform services forming a virtual laboratory. In fact, nowadays many biomedicine studies are dealing with large, distributed, and heterogeneous repositories as well as with computationally demanding analyses, and complex integration techniques are more often required to handle this complexity. The Bio Med Portal is designed to host several medical services and it is able to deploy several analysis algorithms. The scope of this chapter is both to present a Grid application with its own medical use case and to emphasize the benefit that a new Design Paradigm based on Grid could provide to research groups spread in geographically distributed sites.
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Nowadays, many clinical and biomedicine studies need large, distributed, and heterogeneous repositories as well as computationally demanding analysis tools and integration among different levels and disciplines is more often required. In order to maximize the results of such experimental scenarios, Grid based approaches may provide a shared, standardized, and reliable solution both for storage of distributed biomedical data and metadata and for access to distributed analysis tools. This is possible thanks both to specialized software layers called frameworks (based on the principle of interchangeable building blocks), and high added value independent tools (developed to cover specific application requirements). Being perfectly integrated with the official middleware, these tools allow to implement complex service platforms according to a modular architecture, scalable enough for accessing remotely large amounts of distributed data as well as for scaling computational performances on terabyte (1012 bytes) datasets. These frameworks are also implemented to hide the complexity of the underlying Grid Infrastructure at two different levels: end users, to make them able to easily access available services and data for life science research and clinical applications; developers, to better design and implement shared research environments and high added value services and tools.

The BM Portal project, a Grid based software solution thought to promote collaboration and cooperation among scientists and healthcare research groups, enables the remote use of electronic medical instruments integrated in a complex software platform services called virtual laboratory. This project is carried out by the University of Genoa, Department of Communication, Computer and System Sciences, BIOLAB laboratory with the cooperation of some Italian SMEs (Aitek SpA, Nice Srl, R&T enginering Srl, Unico informatica SrL) the INFN (National Institute of Nuclear Physics - department of Catania, www.consorzio-cometa.it) as Grid infrastructure provider and integration support.


Research in life sciences is at an important nexus driven by the generation of large volumes of rapidly expanding data and the capabilities of technology to share distributed data and resources. The core of this nexus affords researchers the opportunity to address large and complex problems and model even entire organisms. Grid technology and high-performance computing provide the ability to process, analyse, store and share data at unprecedented scales. Biomedical applications often require high-performance computing and large data handling which exceeds the computing capacity of a single institution (Krishnan, 2004). Sharing of unpublished data is also important in promoting collaborative research among institutions (Li, Byrnes, Hayes, Birnbaum, Reyes, Shahab, Mosley, Pekurovsky, Quinn, Shindyalov, Casanova, Ang, Berman, Arzberger, Miller, & Bourne, 2004), as well as sharing of public databases, biomedical tools and web services (Umetsu, Ohki, Fukuzaki, Konagaya, Shinbara, Saito, Watanabe, Kitagawa, & Hoshino, 2006; Konishi, Yagi, & Konagaya, 2006). Biological knowledge, such as ontology and metadata, also plays an important role in analysis of experimental data and integration of data coming from different fields such as bioinformatics and neuroinformatics (Cannata, Merelli & Altman, 2005). Grid computing has a great potential to become the standard model for cyberinfrastructures for life sciences and it is a promising information technology which meets the above requirements (Arzberger, Farazdel, Konagaya, Ang, Shimojo & Stevens,2004). However, many features of it remain to be improved in terms of availability, performance and security, to name a few.

Key Terms in this Chapter

Grid Security Infrastructure (GSI): The security infrastructure of a gLite grid middleware

Workflow: A reliably repeatable pattern of activity enabled by a systematic organization of resources, defined roles and mass, energy and information flows, into a work process that can be documented and learned.

Grid Applications: It shares and reuses application code but uses software technologies like service oriented architectures that facilitate sharing business logic among multiple applications.

Grid Computing: A style of computing that dynamically pools IT resources together for use based on resource need. It allows organizations to provision and scale resources as needs arise, thereby preventing the underutilization of resources (computers, networks, data archives, instruments).

EnginFrame: Grid Portal providing an efficient infrastructure to put Grid-empowered applications on your corporate Intranet/Internet.

Single Photon Emission Computed Tomography (SPECT): A nuclear medicine tomographic imaging technique using gamma rays. It is very similar to conventional nuclear medicine planar imaging using a gamma camera. However, it is able to provide true 3D information.

Grid Storage Access Framework (GSAF): Data Access Layer for grid middleware. It is interface that allows business components to manage data stored on the Data Management System and presentation objects to search and retrieve data from it.

Secure Storage Service (SSS): Secure Storage is a grid service that allows users to manage confidential information/data in a Grid environment solving the Insider Abuse problem.

Statistical Parametric Mapping (SPM): An academic software toolkit for the analysis of functional imaging data, for users familiar with the underlying statistical, mathematical and image processing concepts. It examines differences in brain activity recorded during functional neuroimaging experiments, using brain imaging technologies such as or PET.

Positron Emission Tomography (PET): A nuclear medicine medical imaging technique which produces a three-dimensional image or map of functional processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radioisotope, which is introduced into the body on a metabolically active molecule; images of metabolic activity in space are then reconstructed by computer analysis.

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