LEADER 04376nam 22005535 450 001 9910299459303321 005 20200703181949.0 010 $a3-319-73515-2 024 7 $a10.1007/978-3-319-73515-3 035 $a(CKB)4100000002892261 035 $a(MiAaPQ)EBC5357927 035 $a(DE-He213)978-3-319-73515-3 035 $a(PPN)225553384 035 $a(EXLCZ)994100000002892261 100 $a20180301d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLinked Data $eStoring, Querying, and Reasoning /$fby Sherif Sakr, Marcin Wylot, Raghava Mutharaju, Danh Le Phuoc, Irini Fundulaki 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (236 pages) 311 $a3-319-73514-4 327 $a1 Introduction -- 2 Fundamentals -- 3 Centralized RDF Query Processing -- 4 Distributed RDF Query Processing.- 5 Processing of RDF Stream Data -- 6 Distributed Reasoning of RDF Data -- 7 Benchmarking RDF Query Engines and Instance Matching Systems -- 8 Provenance Management for Linked Data -- 9 Conclusions and Outlook. 330 $aThis 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. 606 $aComputers 606 $aArtificial intelligence 606 $aInformation storage and retrieval 606 $aModels and Principles$3https://scigraph.springernature.com/ontologies/product-market-codes/I18016 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aComputers. 615 0$aArtificial intelligence. 615 0$aInformation storage and retrieval. 615 14$aModels and Principles. 615 24$aArtificial Intelligence. 615 24$aInformation Storage and Retrieval. 676 $a025.0427 700 $aSakr$b Sherif$4aut$4http://id.loc.gov/vocabulary/relators/aut$0866736 702 $aWylot$b Marcin$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMutharaju$b Raghava$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLe Phuoc$b Danh$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aFundulaki$b Irini$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910299459303321 996 $aLinked Data$92281701 997 $aUNINA