Semantic Web

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.