Part I: Sharing and Open Research
Implementing a Grid / Cloud e-Science Infrastructure for Hydrological Sciences
The German Grid Initiative: Current State and Future Perspectives
Democratizing Resource-Intensive e-Science Through Peer-to-Peer Grid Computing
Peer4Peer: E-science Communities for Overlay Network and Grid Computing Research
Part II: Data-Intensive e-Science
A Multi-Disciplinary, Model-Driven, Distributed Science Data System Architecture
An Integrated Ontology Management and Data Sharing Framework for Large-Scale Cyberinfrastructure
Part III: Collaborative Research
An e-Science Cyberinfrastructure for Solar-enabled Water Production and Recycling
e-Science Infrastructure Interoperability Guide: The Seven Steps Towards Interoperability for e-Science
Trustworthy Distributed Systems Through Integrity-Reporting
An Intrusion Diagnosis Perspective on Cloud Computing
Part IV: Research Automation, Reusability, Reproducibility and Repeatability
Conventional Workflow Technology for Scientific Simulation
Facilitating E-Science Discovery Using Scientific Workflows on the Grid
Concepts and Algorithms of Mapping Grid-Based Workflows to Resources Within an SLA Context
Orchestrating e-Science with the Workflow Paradigm: Task-Based Scientific Workflow Modelling and Performing
Part V: e-Science: Easy Science
Face Recognition using Global and Local Salient Features
OGSA-Based SOA for Collaborative Cancer Research: System Modelling and Generation
e-Science: The Way Leading to Modernization of Sciences and Technologies