This book describes efficient and effective techniques for harnessing
the power of Linked Data by tackling the various aspects of managing its
growing volume: storing, querying, reasoning, provenance management and
benchmarking.
To this end, Chapter 1 introduces the main concepts of the Semantic Web
and Linked Data and provides a roadmap for the book. Next, Chapter 2
briefly presents the basic concepts underpinning Linked Data
technologies that are discussed in the book. Chapter 3 then offers an
overview of various techniques and systems for centrally querying RDF
datasets, and Chapter 4 outlines various techniques and systems for
efficiently querying large RDF datasets in distributed environments.
Subsequently, Chapter 5 explores how streaming requirements are
addressed in current, state-of-the-art RDF stream data processing.
Chapter 6 covers performance and scaling issues of distributed RDF
reasoning systems, while Chapter 7 details benchmarks for RDF query
engines and instance matching systems. Chapter 8 addresses the
provenance management for Linked Data and presents the different
provenance models developed. Lastly, Chapter 9 offers a brief summary,
highlighting and providing insights into some of the open challenges and
research directions.
Providing an updated overview of methods, technologies and systems
related to Linked Data this book is mainly intended for students and
researchers who are interested in the Linked Data domain. It enables
students to gain an understanding of the foundations and underpinning
technologies and standards for Linked Data, while researchers benefit
from the in-depth coverage of the emerging and ongoing advances in
Linked Data storing, querying, reasoning, and provenance management
systems. Further, it serves as a starting point to tackle the next
research challenges in the domain of Linked Data management.
