Download (direct link):
In general, it is clear that we are only actively managing a small fraction of the total information we produce. The effect of this is lost productivity and reduced revenues. In fact, it is the active management of information that turns it into knowledge by selection, addition, sequence, correlation, and annotation. The purpose of this book is to lay out a clear path to improved knowledge management in your organization using Semantic Web technologies. Second, we examine the technology building blocks of the Semantic Web to include XML, Web services, and RDF. Lastly, not only do we show you how the Semantic Web will be achieved, we provide the justifications and business case on how you can put these technologies to use for a significant return on investment.
Why You Should Read This Book Now
Events become interrelated into trends because of an underlying attractive goal, which individual actors attempt to achieve often only partially. For
The Semantic Web
example, the trend toward electronic device convergence is based on the goal of packing related features together to reduce device cost and improve utility. The trend toward software components is based on the goal of software reuse, which lowers cost and increases speed to market. The trend of do-it-yourself construction is based on the goals of individual empowerment, pride in accomplishment, and reduced cost. The trend toward the Semantic Web is based on the goal of semantic interoperability of data, which enables application independence, improved search facilities, and improved machine inference.
Smart organizations do not ignore powerful trends. Additionally, if the trend affects or improves mission-critical applications, it is something that must be mastered quickly. This is the case with the Semantic Web. The Semantic Web is emerging today in thousands of pilot projects in diverse industries like library science, defense, medicine, and finance. Additionally, technology leaders like IBM, HP, and Adobe have Semantic Web products available, and many more IT companies have internal Semantic Web research projects. In short, key areas of the Semantic Web are beyond the research phase and have moved into the implementation phase.
The Semantic Web dominoes have begun to tumble: from XML to Web services to taxonomies to ontologies to inference. This does not represent the latest fad; instead, it is the culmination of years of research and experimentation in knowledge representation. The impetus now is the success of the World Wide Web. HTML, HTTP, and other Web technologies provide a strong precedent for successful information sharing. The existing Web will not go away; the introduction of Semantic Web technologies will enhance it to include knowledge sharing and discovery.
Our Approach to This Complex Topic
Our model for this book is a conversation between the CIO and CEO in crafting a technical vision for a corporation. In that model, we first explain the concepts in clear terms and illustrate them with concrete examples. Second, we make hard technical judgments on the technology—warts and all. We are not acting as cheerleaders for this technology. Some of it can be better, and we point out the good, the bad, and the ugly. Lastly, we lay the cornerstones of a technical policy and tie it all together in the final chapter of the book.
Our model for each subject was to provide straightforward answers to the key questions on each area. In addition, we provide concrete, compelling examples of all key concepts presented in the book. Also, we provide numerous illustrative diagrams to assist in explaining concepts. Lastly, we present several new
concepts of our own invention, leveraging our insight into these technologies, how they will evolve, and why.
How This Book Is Organized
This book is composed of nine chapters that can be read either in sequence or
as standalone units:
Chapter 1, What Is the Semantic Web? This chapter explains the Semantic Web vision of creating machine-processable data and how we achieve that vision. Explains the general framework for achieving the Semantic Web, why we need the Semantic Web, and how the key technologies in the rest of the book fit into the Semantic Web. This chapter introduces novel concepts like the smart-data continuum and combinatorial experimentation.
Chapter 2, The Business Case for the Semantic Web. This chapter clearly demonstrates concrete examples of how businesses can leverage the Semantic Web for competitive advantage. Specifically, presents examples on decision support, business development, and knowledge management. The chapter ends with a discussion of the current state of Semantic Web technology.
Chapter 3, Understanding XML and Its Impact on the Enterprise. This chapter explains why XML is a success, what XML is, what XML Schema is, what namespaces are, what the Document Object Model is, and how XML impacts enterprise information technology. The chapter concludes with a discussion of why XML meta data is not enough and the trend toward higher data fidelity. Lastly, we close by explaining the new concept of semantic levels. For any organization not currently involved in integrating XML throughout the enterprise, this chapter is a must-read.