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Guide to e-Science

Next Generation Scientific Research and Discovery

By Xiaoyu Yang , Lizhe Wang , Wei Jie

Guide to e-Science Cover Image

Using real-world examples, this book shows how computational technologies and tools can be used to build essential infrastructures supporting next-generation scientific research. Covers security, privacy, collaboration, automated workflow technology and more.

Full Description

  • ISBN13: 978-0-8572-9438-8
  • 565 Pages
  • User Level: Science
  • Publication Date: May 26, 2011
  • Available eBook Formats: PDF
  • eBook Price: $159.00
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Full Description
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.
Table of Contents

Table of Contents

  1. Part I: Sharing and Open Research.
  2. Implementing a Grid / Cloud e
  3. Science Infrastructure for Hydrological Sciences.
  4. The German Grid Initiative.
  5. Democratizing Resource
  6. Intensive e
  7. Science Through Peer
  8. to
  9. Peer Grid Computing.
  10. Peer4Peer: E
  11. science Communities for Overlay Network and Grid Computing Research.
  12. Part II: Data
  13. Intensive e
  14. Science.
  15. A Multi
  16. Disciplinary, Model
  17. Driven, Distributed Science Data System Architecture.
  18. An Integrated Ontology Management and Data Sharing Framework for Large
  19. Scale Cyberinfrastructure.
  20. Part III: Collaborative Research.
  21. An e
  22. Science Cyberinfrastructure for Solar
  23. enabled Water Production and Recycling.
  24. e
  25. Science Infrastructure Interoperability Guide.
  26. Trustworthy Distributed Systems Through Integrity
  27. Reporting.
  28. An Intrusion Diagnosis Perspective on Cloud Computing.
  29. Part IV: Research Automation, Reusability, Reproducibility and Repeatability.
  30. Conventional Workflow Technology for Scientific Simulation.
  31. Facilitating E
  32. Science Discovery Using Scientific Workflows on the Grid.
  33. Concepts and Algorithms of Mapping Grid
  34. Based Workflows to Resources Within an SLA Context.
  35. Orchestrating e
  36. Science with the Workflow Paradigm.
  37. Part V: e
  38. Science: Easy Science.
  39. Face Recognition using Global and Local Salient Features.
  40. OGSA
  41. Based SOA for Collaborative Cancer Research.
  42. e
  43. Science.
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