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Abstract

This book shows you how to harness the power of linked data and web-scale discovery systems to manage and link widely varied content across your library collection. Libraries are increasingly using web-scale discovery systems to help clients find a wide assortment of library materials, including books, journal articles, special collections, archival collections, videos, music and open access collections. Depending on the library material catalogued, the discovery system might need to negotiate different metadata standards, such as AACR, RDA, RAD, FOAF, VRA Core, METS, MODS, RDF and more. In Managing Metadata in Web-Scale Discovery Systems, editor Louise Spiteri and a range of international experts show you how to: * maximize the effectiveness of web-scale discovery systems * provide a smooth and seamless discovery experience to your users * help users conduct searches that yield relevant results * manage the sheer volume of items to which you can provide access, so your users can actually find what they need * maintain shared records that reflect the needs, languages, and identities of culturally and ethnically varied communities * manage metadata both within, across, and outside, library discovery tools by converting your library metadata to linked open data that all systems can access * manage user generated metadata from external services such as Goodreads and LibraryThing * mine user generated metadata to better serve your users in areas such as collection development or readers' advisory. The book will be essential reading for cataloguers, technical services and systems librarians and library and information science students studying modules on metadata, cataloguing, systems design, data management, and digital libraries. The book will also be of interest to those managing metadata in archives, museums and other cultural heritage institutions.

Content

1. Introduction: the landscape of web-scale discovery - Louise Spiteri 2. Sharing metadata across discovery systems - Marshall Breeding, Angela Kroeger and Heather Moulaison Sandy 3. Managing linked open data across discovery systems - Ali Shiri and Danoosh Davoodi 4. Redefining library resources in discovery systems - Christine DeZelar-Tiedman 5. Managing volume in discovery systems - Aaron Tay 6. Managing outsourced metadata in discovery systems - Laurel Tarulli 7. Managing user-generated metadata in discovery systems - Louise Spiteri

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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.

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Date

23. 7.2017 13:49:22