Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 141-157).

Preface -- 1. Role of semantics and metadata -- 1.1 Web 1.0, web 2.0, web 3.0 --

2. Types and models of semantics -- 2.1 Types of semantics -- 2.1.1 Implicit semantics -- 2.1.2 Formal semantics -- 2.1.3 Powerful (soft) semantics -- 2.2 Applications and types of semantics they exploit -- 2.2.1 Retrieval applications: information vs. data -- 2.2.2 Data mining applications -- 2.2.3 Analytical applications -- 2.3 Models of semantics -- 2.3.1 Prescriptive approaches summary -- 2.3.2 Descriptive approaches summary -- 2.4 Ontology and ontology development -- 2.4.1 What is an ontology? -- 2.4.2 How do we develop an ontology? -- 2.4.3 Class vs. property (attribute/relationship) -- 2.4.4 Class vs. instance -- 2.5 A word about practice --

3. Annotation, adding semantics to data -- 3.1 Different forms of data and their semantics -- 3.1.1 Unstructured data -- 3.1.2 Semi-structured data -- 3.1.3 Structured data -- 3.1.4 Multimedia data -- 3.2 Role of semantic metadata -- 3.3 Approaches to adding semantics to data -- 3.3.1 Microformats -- 3.3.2 XLink and model reference -- 3.3.3 RDFa -- 3.3.4 Microdata -- 3.3.5 SA-REST: semantically enhancing RESTful services and resources -- 3.3.6 A standards-based approach to specifying extraction of RDF triples -- 3.3.7 Summing it all up --

4. Semantics for enterprise data -- 4.1 Nature of enterprise content and processing -- 4.2 Role of semantics in the enterprise -- 4.3 Creation of semantic metadata: models and annotations -- 4.3.1 Linking enterprise data -- 4.3.2 Semantic metadata in eScience -- 4.3.3 Semantic techniques in eScience -- 4.4 Examples of semantic enterprise applications --

5. Semantics for services -- 5.1 Nature of web services -- 5.2 Role of semantics in web services -- 5.3 Creation of semantic metadata: models and annotations -- 5.3.1 Top-down approach exemplified -- 5.3.2 Bottom-up approach exemplified -- 5.4 Example applications of semantically annotated web services --

6. Semantics for sensor data -- 6.1 Nature of sensor data -- 6.2 Role of semantics in sensor networks: space, time, and theme -- 6.3 Creation of semantic metadata: models and annotations -- 6.3.1 Semantic annotation -- 6.3.2 Ontologies -- 6.3.3 Semantic sensor network ontology -- 6.3.4 Rule-based reasoning -- 6.3.5 Querying semantic sensor web -- 6.4 Examples of semantic applications --

7. Semantics for social data -- 7.1 Nature of social data -- 7.2 Role of semantics in social media -- 7.3 Creation/application of semantic metadata: models and annotations -- 7.3.1 Disambiguating entity mentions -- 7.3.2 Identifying entities -- 7.3.3 Robustness with respect to off-topic noise -- 7.3.4 Analyzing user comments -- 7.3.5 Aggregating attention metadata -- 7.3.6 Annotating and reasoning with social media -- 7.3.7 The BBC SoundIndex application -- 7.3.8 Harnessing Twitter: Twitris and Twarql applications --

8. Semantics for cloud computing -- 8.1 Nature of cloud services -- 8.2 Role of semantic modeling in cloud computing -- 8.3 Creation and application of semantic metadata: models and annotations -- 8.3.1 Semantics for logical and process portability -- 8.3.2 Semantics for data modeling -- 8.3.3 Semantics for service enrichment -- 8.4 Examples of applications --

9. Semantics for advanced applications -- 9.1 Robust integration of sensors data: reconciling semantic heterogeneity -- 9.2 Spatio-temporal slicing and thematic filtering: achieving scalability -- 9.3 Dynamic model creation and update: continuous semantics -- 9.4 Role of semantics in web of things (cyber-physical systems) -- 9.4.1 Semantics empowered physical-cyber-social systems --

Bibliography -- Authors' biographies.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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After the traditional document-centric Web 1.0 and user-generated content focused Web 2.0, Web 3.0 has become a repository of an ever growing variety of Web resources that include data and services associated with enterprises, social networks, sensors, cloud, as well as mobile and other devices that constitute the Internet of Things. These pose unprecedented challenges in terms of heterogeneity (variety), scale (volume), and continuous changes (velocity), as well as present corresponding opportunities if they can be exploited. Just as semantics has played a critical role in dealing with data heterogeneity in the past to provide interoperability and integration, it is playing an even more critical role in dealing with the challenges and helping users and applications exploit all forms of Web 3.0 data. This book presents a unified approach to harness and exploit all forms of contemporary Web resources using the core principles of ability to associate meaning with data through conceptual or domain models and semantic descriptions including annotations, and through advanced semantic techniques for search, integration, and analysis. It discusses the use of Semantic Web standards and techniques when appropriate, but also advocates the use of lighter weight, easier to use, and more scalable options when they are more suitable. The authors' extensive experience spanning research and prototypes to development of operational applications and commercial technologies and products guide the treatment of the material.

Also available in print.

Title from PDF t.p. (viewed on January 18, 2013).