Linked Data Management

Linked Data Management presents techniques for querying and managing Linked Data that is available on today’s Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications.

The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to Linked Data and related standards, including the main principles distinguishing Linked Data from standard database technology. Chapters also describe how to generate links between datasets and explain the overall architecture of data integration systems based on Linked Data.

A large part of the text is devoted to query processing in different setups. After presenting methods to publish relational data as Linked Data and efficient centralized processing, the book explores lookup-based, distributed, and parallel solutions. It then addresses advanced topics, such as reasoning, and discusses work related to read-write Linked Data for system interoperation.

Despite the publication of many papers since Tim Berners-Lee developed the Linked Data principles in 2006, the field lacks a comprehensive, unified overview of the state of the art. Suitable for both researchers and practitioners, this book provides a thorough, consolidated account of the new data publishing and data integration paradigm. While the book covers query processing extensively, the Linked Data abstraction furnishes more than a mechanism for collecting, integrating, and querying data from the open Web—the Linked Data technology stack also allows for controlled, sophisticated applications deployed in an enterprise environment.

Table of Contents

Part I: Introduction
Chapter 1: Linked Data & the Semantic Web Standards
Chapter 2: Aligning Ontologies of Linked Data
Chapter 3: Architecture of Linked Data Applications

Part II: Centralized Query Processing
Chapter 4: Mapping Relational Databases to Linked Data
Chapter 5: Efficient Query Processing in RDF Databases
Chapter 6: Evaluating SPARQL Queries over Linked Data Streams

Part III: Parallel Query Processing
Chapter 7: SPARQL Query Processing in the Cloud
Chapter 8: The Bigdata® RDF Graph Database
Chapter 9: Experiences with Virtuoso Cluster RDF Column Store

Part IV: Distributed Query Processing
Chapter 10: Linked Data Query Processing Based on Link Traversal
Chapter 11: Semantic Navigation on the Web of Data
Chapter 12: Index-Based Source Selection and Optimization
Chapter 13: P2P-Based Query Processing over Linked Data
Chapter 14: Federated Query Processing over Linked Data

Part V: Reasoning over RDF Data
Chapter 15: On the Use of Abstract Models for RDF/S Provenance
Chapter 16: Incremental Reasoning on RDF Streams

Part VI: Linked Data Interfaces
Chapter 17: Linked Data Services
Chapter 18: Using read-write Linked Data for Application Integration