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Abstract

This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.

Content

Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining

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Abstract

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.