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Añadir al carritoTaschenbuch. Condición: Neu. Real-time Linked Dataspaces | Enabling Data Ecosystems for Intelligent Systems | Edward Curry | Taschenbuch | xxiii | Englisch | 2020 | Springer | EAN 9783030296674 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Idioma: Inglés
Publicado por Springer International Publishing Sep 2020, 2020
ISBN 10: 3030296679 ISBN 13: 9783030296674
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems. It establishes the theoretical foundations and principles of real-time linked dataspaces as a data platform for intelligent systems. The book introduces a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration for managing and processing events and streams.The book is divided into five major parts: Part I 'Fundamentals and Concepts' details the motivation behind and core concepts of real-time linked dataspaces, and establishes the need to evolve data management techniques in order to meet the challenges of enabling data ecosystems for intelligent systems within smart environments. Further, it explains the fundamental concepts of dataspaces and the need for specialization in the processing of dynamic real-time data. Part II 'Data Support Services' explores the design and evaluation of critical services, including catalog, entity management, query and search, data service discovery, and human-in-the-loop. In turn, Part III 'Stream and Event Processing Services' addresses the design and evaluation of the specialized techniques created for real-time support services including complex event processing, event service composition, stream dissemination, stream matching, and approximate semantic matching. Part IV 'Intelligent Systems and Applications' explores the use of real-time linked dataspaces within real-world smart environments. In closing, Part V 'Future Directions' outlines future research challenges for dataspaces, data ecosystems, and intelligent systems.Readers will gain a detailed understanding of how the dataspace paradigm is now being used to enable data ecosystems for intelligent systems within smart environments. The book covers the fundamental theory, the creation of new techniques needed for support services, and lessons learned from real-world intelligentsystems and applications focused on sustainability. Accordingly, it will benefit not only researchers and graduate students in the fields of data management, big data, and IoT, but also professionals who need to create advanced data management platforms for intelligent systems, smart environments, and data ecosystems. 352 pp. Englisch.
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Añadir al carritoCondición: New. Print on Demand pp. XXIII, 325 111 illus., 30 illus. in color.
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. XXIII, 325 111 illus., 30 illus. in color.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030296679 ISBN 13: 9783030296674
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Open AccessEstablishes the theoretical foundations and principles of real-time linked dataspaces as a data platform for intelligent systemsIntroduces specialized best-effort techniques and models to enable incremental.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Sep 2020, 2020
ISBN 10: 3030296679 ISBN 13: 9783030296674
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems. It establishes the theoretical foundations and principles of real-time linked dataspaces as a data platform for intelligent systems. The book introduces a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration for managing and processing events and streams.The book is divided into five major parts: Part I 'Fundamentals and Concepts' details the motivation behind and core concepts of real-time linked dataspaces, and establishes the need to evolve data management techniques in order to meet the challenges of enabling data ecosystems for intelligent systems within smart environments. Further, it explains the fundamental concepts of dataspaces and the need for specialization in the processing of dynamic real-time data. Part II 'Data Support Services' explores the design and evaluation of critical services, including catalog, entity management, query and search, data service discovery, and human-in-the-loop. In turn, Part III 'Stream and Event Processing Services' addresses the design and evaluation of the specialized techniques created for real-time support services including complex event processing, event service composition, stream dissemination, stream matching, and approximate semantic matching. Part IV 'Intelligent Systems and Applications' explores the use of real-time linked dataspaces within real-world smart environments. In closing, Part V 'Future Directions' outlines future research challenges for dataspaces, data ecosystems, and intelligent systems.Readers will gain a detailed understanding of how the dataspace paradigm is now being used to enable data ecosystems for intelligent systems within smart environments. The book covers the fundamental theory, the creation of new techniques needed for support services, and lessons learned from real-world intelligent systems and applications focused on sustainability. Accordingly, it will benefit not only researchers and graduate students in the fields of data management, big data, and IoT, but also professionals who need to create advanced data management platforms for intelligent systems, smart environments, and data ecosystems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 352 pp. Englisch.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems. It establishes the theoretical foundations and principles of real-time linked dataspaces as a data platform for intelligent systems. The book introduces a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration for managing and processing events and streams.The book is divided into five major parts: Part I 'Fundamentals and Concepts' details the motivation behind and core concepts of real-time linked dataspaces, and establishes the need to evolve data management techniques in order to meet the challenges of enabling data ecosystems for intelligent systems within smart environments. Further, it explains the fundamental concepts of dataspaces and the need for specialization in the processing of dynamic real-time data. Part II 'Data Support Services' explores the design and evaluation of critical services, including catalog, entity management, query and search, data service discovery, and human-in-the-loop. In turn, Part III 'Stream and Event Processing Services' addresses the design and evaluation of the specialized techniques created for real-time support services including complex event processing, event service composition, stream dissemination, stream matching, and approximate semantic matching. Part IV 'Intelligent Systems and Applications' explores the use of real-time linked dataspaces within real-world smart environments. In closing, Part V 'Future Directions' outlines future research challenges for dataspaces, data ecosystems, and intelligent systems.Readers will gain a detailed understanding of how the dataspace paradigm is now being used to enable data ecosystems for intelligent systems within smart environments. The book covers the fundamental theory, the creation of new techniques needed for support services, and lessons learned from real-world intelligentsystems and applications focused on sustainability. Accordingly, it will benefit not only researchers and graduate students in the fields of data management, big data, and IoT, but also professionals who need to create advanced data management platforms for intelligent systems, smart environments, and data ecosystems.