Enterprise data is growing at a much faster rate than traditional technologies allow. The World Wide Web is the only information system that scales to the degree that it does and is robust to both changes and failure of components. Most software does not work nearly as well as the Web does. Applying the Web's architectural principles (versus using the public Web directly) for enterprise problems maybe the only way to effectively address the current and future information glut.
Linking Enterprise Data is an edited volume contributed by worldwide leaders in Semantic Web research, standards development and early adopters of Semantic Web standards and techniques. Linking enterprise data is the application of World Wide Web architecture principles to real-world information management issues faced by commercial, not-for-profit and government enterprises. The first section of this book will address business, technical and social values of applying Web architecture to enterprise content. An important focus of the first section will be the building of social (human-centered) communities to curate distributed data. The second section, Infrastructure, will address the need and options for persistent identifiers of data, terms and vocabularies for use by enterprise architects, and data storage and retrieval infrastructure appropriate for use. Case studies and examples that demonstrate the applicability of the proposed architectures are presented in the last section of Linking Enterprise Data.
About this book:
- Provides practical approaches to addressing common information management issues by the application of leading edge research.
- Application approaches are based on international standards.
- Includes case studies and examples that demonstrate the applicability of the proposed architectures.
This book targets professionals working as CTOs, CIOs, enterprise architects, project managers and application developers in commercial, not-for-profit and government organizations concerned with scalability, flexibility and robustness of information management systems and the Semantic Web. Advanced-level students and researchers focusing on computer science will also find this book valuable as a secondary text or reference book.
