Semantic e-Science

Cover13; -- Preface -- Contents -- Contributors -- About the Editors -- Chapter 1 Supporting e-Science Using Semantic Web Technologies The Semantic Grid -- 1.1 Introduction -- 1.2 The e-Science Vision -- 1.3 Semantic Grid: Service-Oriented Science -- 1.4 Semantic Web Essentials -- 1.5 Achieving the e-Science Vision -- 1.5.1 Resource Description, Discovery, and Use -- 1.5.2 Process Description and Enactment -- 1.5.3 Autonomic Behaviour -- 1.5.4 Security and Trust -- 1.5.5 Annotation -- 1.5.6 Information Integration -- 1.5.7 Communities -- 1.6 A Semantic Grid Approach to In Silico Bioinformatics -- 1.7 A Semantic Datagrid for Chemistry -- 1.8 Architectures for the Semantic Grid -- 1.8.1 S-OGSA -- A Reference Architecture for the Semantic Grid -- 1.8.2 The Service-Oriented Knowledge Utility -- 1.8.3 The Semantic Grid Community -- 1.9 Moving Forward -- 1.10 Summary -- References -- Chapter 2 Semantic Disclosure in an e-Science Environment -- 2.1 Introduction -- 2.1.1 Semantic Disclosure -- 2.1.2 The Semantic Web -- 2.1.3 Making Sense of the Digital Deluge -- 2.1.4 Data Integration -- 2.1.5 W3C Semantic Web for Health Care and Life Sciences Interest Group -- 2.1.6 Semantic Architecture -- 2.1.7 The Virtual Laboratory for e-Science Project -- 2.2 The AIDA Toolkit -- 2.2.1 Storage -- The Metadata Storage Module -- 2.2.2 Learning -- The Machine Learning Module -- 2.2.3 Search -- The Information Retrieval Module -- 2.3 Applications of Adaptive Information Disclosure -- 2.3.1 Food Informatics -- Adaptive Information Disclosure Collaboration -- 2.3.2 A Metadata Management Approach to fMRI Data -- 2.3.3 Semantic Disclosure in Support of Biological Experimentation -- 2.4 Discussion -- References -- Chapter 3 A Smart e-Science Cyberinfrastructure for Cross-Disciplinary Scientific Collaborations -- 3.1 Introduction -- 3.2 Background -- 3.2.1 Challenges for Smart e-Science -- 3.2.2 Enabling Technologies for Smart e-Science -- 3.2.3 Contemporary Efforts in e-Science Cyberinfrastructure -- 3.2.4 Case Study: Integration of Scientific Infrastructures -- 3.3 The Smart e-Science Framework -- 3.3.1 The e-Science Ontology -- 3.3.2 Grid-Based Service Orientation -- 3.3.3 Service Interface -- 3.3.4 Semantic Interface -- 3.3.5 The Proxy -- 3.3.6 Knowledgebase Design -- 3.3.7 Data Exchange -- 3.4 Implementation -- 3.4.1 Ontology Design -- 3.4.2 Server-Side Service Implementation -- 3.4.3 Client-Side Service Implementation -- 3.4.4 Fundamental and Composed Services -- 3.4.5 Conceptual and Semantic Schema -- 3.5 Conclusions -- References -- Chapter 4 Developing Ontologies within Decentralised Settings -- 4.1 Introduction -- 4.1.1 Decentralised Communities -- 4.1.2 Community-Driven Ontology Engineering -- 4.1.3 Upper Level Ontologies -- 4.1.4 Dynamic Ontologies -- 4.1.5 The Melting Point: A Methodology for Distributed Community-Driven Ontology Engineering -- 4.2 Review of Current Methodologies -- 4.2.1 Criteria for Review -- 4.2.2 Finding the Melting Point -- 4.3 The Melting Point Methodology -- 4.3.1 Definition of Terminology -- 4.3.2 Management Processes -- 4.3.3 Documentation Processes -- 4.3.4 Development-Oriented Processes -- 4.3.5 Evaluation -- 4.4 Discussion -- 4.4.1 Melting Point Evaluated -- 4.4.2 IEEE Standards Compliance -- 4.4.3 Quality Ass.