This guidebook on e-science presents real-world examples of practices and applications, demonstrating how a range of computational technologies and tools can be employed to build essential infrastructures supporting next-generation scientific research. Each chapter provides introductory material on core concepts and principles, as well as descriptions and discussions of relevant e-science methodologies, architectures, tools, systems, services and frameworks. Features: includes contributions from an international selection of preeminent e-science experts and practitioners; discusses use of mainstream grid computing and peer-to-peer grid technology for "open" research and resource sharing in scientific research; presents varied methods for data management in data-intensive research; investigates issues of e-infrastructure interoperability, security, trust and privacy for collaborative research; examines workflow technology for the automation of scientific processes; describes applications of e-science.

InhaltsangabePart I: Sharing and Open ResearchImplementing a Grid / Cloud e-Science Infrastructure for Hydrological SciencesThe German Grid Initiative: Current State and Future PerspectivesDemocratizing Resource-Intensive e-Science Through Peer-to-Peer Grid ComputingPeer4Peer: E-science Communities for Overlay Network and Grid Computing ResearchPart II: Data-Intensive e-ScienceA Multi-Disciplinary, Model-Driven, Distributed Science Data System ArchitectureAn Integrated Ontology Management and Data Sharing Framework for Large-Scale CyberinfrastructurePart III: Collaborative ResearchAn e-Science Cyberinfrastructure for Solar-enabled Water Production and Recyclinge-Science Infrastructure Interoperability Guide: The Seven Steps Towards Interoperability for e-ScienceTrustworthy Distributed Systems Through Integrity-ReportingAn Intrusion Diagnosis Perspective on Cloud ComputingPart IV: Research Automation, Reusability, Reproducibility and RepeatabilityConventional Workflow Technology for Scientific SimulationFacilitating E-Science Discovery Using Scientific Workflows on the GridConcepts and Algorithms of Mapping Grid-Based Workflows to Resources Within an SLA ContextOrchestrating e-Science with the Workflow Paradigm: Task-Based Scientific Workflow Modelling and PerformingPart V: e-Science: Easy ScienceFace Recognition using Global and Local Salient FeaturesOGSA-Based SOA for Collaborative Cancer Research: System Modelling and Generatione-Science: The Way Leading to Modernization of Sciences and Technologies