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.

This book constitutes the refereed proceedings of the 18th International Semantic Web Conference, ESWC 2021, held virtually in June 2021. The 41 full papers and 2 short papers presented were carefully reviewed and selected from 167 submissions. The papers were submitted to three tracks: the research track, the resource track and the in-use track. These tracks showcase research and development activities, services and applications, and innovative research outcomes making their way into industry. The research track caters to both long-standing and emerging research topics in the form of the following subtracks: ontologies and reasoning; knowledge graphs (understanding, creating, and exploiting); semantic data management, querying and distributed data; data dynamics, quality, and trust; matching, integration, and fusion; NLP and information retrieval; machine learning; science data and scholarly communication; and problems to solve before you die.

This book constitutes the proceedings of the satellite events held at the 17th Extended Semantic Web Conference, ESWC 2020, in May/June 2020. The conference was planned to take place in Heraklion, Crete, Greece, but changed to an online format due to the COVID-19 pandemic. ESWC is a major venue for presenting and discussing the latest scientific results and technology innovations related to the Semantic Web, Linked Data and Knowledge Graphs. The 36 poster and demo papers, 7 PhD symposium papers, and 4 industry track papers, included in this volume were carefully reviewed and selected from 59 submissions to the poster and demo track; 11 submissions to the PhD symposium track, and 5 submissions to the Industry track.

This book constitutes the thoroughly refereed post-conference proceedings of the Satellite Events of the 14th European Conference on the Semantic Web, ESWC 2017, held in Portoroz, Slovenia, in May/June2017.The volume contains 8 poster and 24 demonstration papers, selected from 105 submissions. Additionally, this book includes a selection of 13 best workshop papers. The papers cover various aspects of the semantic web.The chapter 'Scholia, Scientometrics and Wikidata' is available open access under a CC BY 4.0 license via link.springer.com.