Main description:

The rapid growth of the Web has led to the proliferation of information sources and content accessible via the Internet. While improvements in hardware capabilities continue to help the speed and the flow of information across networked computers, there remains a major problem for the human user to keep up with the rapid expansion of the Web information space. Although there is plenty of room for computers to help humans to discover, navigate, and integrate information in this vast information space, the way the information is currently represented and structured through the Web is not easily readable to computers. To address this issue, the Semantic Web has emerged. It envisions a new information infrastructure that enables computers to better address the information needs of human users. To realize the Semantic Web vision, a number of standard technologies have been developed. These include the Uniform Resource Identifiers (URI) for identifying objects in the Web space as well as Resource Description Framework (RDF) and Web Ontology Language (OWL) for encoding knowledge in the form of standard machine-readable ontologies. The goal is to migrate from the syntactic Web of documents to the semantic Web of ontologies. The leading organization for facilitating, developing, and promoting these Web-based standards is the World Wide Web Consortium (W3C) (http://www. w3. org).

Feature:

Covers topics ranging from database, ontology, visualization, to semantic web services and workflows

Features the intersection of Semantic Web and Life Sciences

Gives examples/scenarios illustrating different Semantic Web applications in the life science domain

Discusses the limitations and obstacles that need to be overcome for Semantic Web to better meet the current and future needs of life science researchers

Back cover:

The Semantic Web is now a research discipline in its own right and commercial interest in applications of Semantic Web technologies is strong. The advantages of the Semantic Web lie in its ability to present and provide access to complex knowledge in a standardized form making interoperability between distributed databases and middleware achievable.

Life Scientists have much to gain from the emergence of the Semantic Web since their work is strongly knowledge-based. Unambiguous, semantically-rich, structured declarations of information have long been a fundamental cornerstone of scientific discourse. To have such information available in machine-readable form makes a whole new generation of scientific software possible. The value that the Semantic Web offers to the Life Sciences is currently under appreciated. A pedagogical oasis is required for interested scientists and bioinformatics professionals, where they can learn about and draw inspiration from the Semantic Web and its component technologies. In this context this book seeks to offer students, researchers, and professionals a glimpse of the technology, its capabilities and the reach of its current implementation in the Life Sciences. This collection of representative topics, written by leading experts, documents important and encouraging first steps showing the utility of the Semantic Web to Life Science research.

Semantic Web: Revolutionizing Knowledge Discovery in Life Sciences is divided into six parts that cover the topics of: knowledge integration, knowledge representation, knowledge visualization, utilization of formal knowledge representations, and access to distributed knowledge. The final part considers the viability of the semantic web in life science and the legal challenges that will impact on its establishment.

This book may be approached from technical, scientific or application specific perspectives. Component technologies of the Semantic Web (including RDF databases, ontologies, ontological languages, agent systems and web services) are described throughout the book. They are the basic building blocks for creating the Semantic Web infrastructure. Other technologies, such as natural language processing and text mining, which are becoming increasingly important to the Semantic Web, are also discussed. Scientists reading the book will see that the complex needs of biology and medicine are being addressed. Moreover, pioneering Life Scientists have joined forces with Semantic Web developers to build valuable semantic resources for the scientific community. Different areas of computer science (e.g., artificial intelligence, database integration, and visualization) are also being recruited to advance this vision. The ongoing synergy between the Life Sciences and Computer Science is poised to deliver revolutionary discovery tools and new capabilities.

As well as providing the background material and critical evaluation criteria for the design and use of meaningful Semantic Web implementations a multitude of examples are provided. These illustrate the diversity of life science tasks that are benefiting from the use of Semantic Web infrastructure and serve to demonstrate the great potential of the Semantic Web in the Life Sciences.

Contents:

Introduction.- Part I: Database and Literature Integration.- Semantic Web Approach to Database Integration in the Life Sciences.- Querying Semantic Web Contents.- Knowledge Acquisition from the Biomedical Literature.- Part II: Biological Ontologies - Clinical Ontologies for Discovery Applications.- Ontology Engineering for Biological Applications.- The Evaluation of Ontologies: Toward Improved Semantic Interoperability.- OWL for the Novice: A Logical Perspective.- PART III: Ontology Visualization.- Techniques for Ontology Visualization.- On Visualization of OWL Ontologies.- PART IV: Ontologies in Action.- Applying OWL Reasoning to Genomics.- Can Semantic Web Technologies Enable Translational Medicine?.- Ontology Design for Biomedical Text Mining.- PART V: Using Distributed Knowledge.- SemBOWSER Semantic Biological Web Services Registry.- Agent Technologies in the Life Sciences.- Knowledge Discovery for Biology with Taverna.- PART VI: On the Success of Semantic Web in the Life Sciences.- Factors Influencing the Adoption of the Semantic Web in the Life Sciences.- Semantic Web Standards: Legal and Social Issues and Implications.