Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.

This professional book provides a series of case studies which give examples of real benefits to be derived from the adoption of semantic web based ontologies in real world situations, such as telecommunication, B2B integration, tourism, education and more. The book is designed to create platforms for bringing experts together (key government representatives, industry and academia) from different countries, and to compile the most recent use of semantics and ontologies.

The Web is growing at an astounding pace surpassing the 8 billion page mark. However, most pages are still designed for human consumption and cannot be processed by machines. This book provides a well-paced introduction to the Semantic Web. It covers a wide range of topics, from new trends (ontologies, rules) to existing technologies (Web Services and software agents) to more formal aspects (logic and inference). It includes: real-world (and complete) examples of the application of Semantic Web concepts; how the technology presented and discussed throughout the book can be extended to other application areas.

Semantics, Web services, and Web processes promise better re-use, universal interoperability and integration. Semantics has been recognized as the primary tool to address the challenges of a broad spectrum of heterogeneity and for improving automation through machine understandable descriptions. Semantic Web Services, Processes and Applications brings contributions from researchers who study, explore and understand the semantic enabling of all phases of semantic Web processes. This encompasses design, annotation, discovery, choreography and composition. Also this book presents fundamental capabilities and techniques associated with ontological modeling or services, annotation, matching and mapping, and reasoning. This is complemented by discussion of applications in e-Government and bioinformatics. Special bulk rates are available for course adoption through Publishing Editor.

The next major advance in the Web-Web 3.0-will be built on semantic Web technologies, which will allow data to be shared and reused across application, enterprise, and community boundaries. Written by a team of highly experienced Web developers, this book explains examines how this powerful new technology can unify and fully leverage the ever-growing data, information, and services that are available on the Internet. Helpful examples demonstrate how to use the semantic Web to solve practical, real-world problems while you take a look at the set of design principles, collaborative working groups, and technologies that form the semantic Web. The companion Web site features full code, as well as a reference section, a FAQ section, a discussion forum, and a semantic blog.

Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web. It reveals how social network mining from the web plays an important role for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.