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Materializing the Web of Linked Data 2015 ed. [Kõva köide]

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  • Formaat: Hardback, 133 pages, kõrgus x laius: 235x155 mm, kaal: 3495 g, 28 Illustrations, black and white; XIV, 133 p. 28 illus., 1 Hardback
  • Ilmumisaeg: 21-Apr-2015
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319160737
  • ISBN-13: 9783319160733
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  • Kõva köide
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Materializing the Web of Linked Data 2015 ed.Suurem pilt
  • Formaat: Hardback, 133 pages, kõrgus x laius: 235x155 mm, kaal: 3495 g, 28 Illustrations, black and white; XIV, 133 p. 28 illus., 1 Hardback
  • Ilmumisaeg: 21-Apr-2015
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319160737
  • ISBN-13: 9783319160733
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319160733.html
Märksõnad:
This book explains the Linked Data domain by adopting a bottom-up approach: it introduces the fundamental Semantic Web technologies and building blocks, which are then combined into methodologies and end-to-end examples for publishing datasets as Linked Data, and use cases that harness scholarly information and sensor data. It presents how Linked Data is used for web-scale data integration, information management and search. Special emphasis is given to the publication of Linked Data from relational databases as well as from real-time sensor data streams. The authors also trace the transformation from the document-based World Wide Web into a Web of Data. Materializing the Web of Linked Data is addressed to researchers and professionals studying software technologies, tools and approaches that drive the Linked Data ecosystem, and the Web in general.
1 Introduction: Linked Data and the Semantic Web
1(16)
1.1 The Origin of the Semantic Web
1(2)
1.1.1 Why a Semantic Web?
1(1)
1.1.2 The Need for Adding Semantics
2(1)
1.2 Preliminaries
3(14)
1.2.1 Data, Information, Knowledge
3(1)
1.2.2 Interoperability, Integration, Merging and Mapping
4(3)
1.2.3 Semantic Annotation
7(1)
1.2.4 Metadata
7(2)
1.2.5 Ontologies
9(1)
1.2.6 Reasoners
10(1)
1.2.7 Knowledge Bases
11(2)
1.2.8 Linked (Open) Data
13(2)
References
15(2)
2 Technical Background
17(34)
2.1 Introduction
17(1)
2.2 The Underlying Technologies
18(1)
2.3 Modeling Data Using RDF Graphs
19(11)
2.3.1 Using Namespaces
20(1)
2.3.2 RDF Serialization
21(5)
2.3.3 The RDF Schema
26(4)
2.4 Ontologies Based on Description Logics
30(5)
2.4.1 Description Logics
30(3)
2.4.2 The Web Ontology Language (OWL)
33(2)
2.5 Querying the Semantic Web with SPARQL
35(4)
2.6 Mapping Relational Data to RDF
39(5)
2.7 Other Technologies
44(2)
2.8 Ontologies and Datasets
46(5)
References
49(2)
3 Deploying Linked Open Data: Methodologies and Software Tools
51(22)
3.1 Introduction
51(1)
3.2 The O in LOD: Open Data
52(4)
3.2.1 Opening Data: Bulk Access vs. API
55(1)
3.2.2 The 5-Star Deployment Scheme
55(1)
3.3 The D in LOD: Modeling Content
56(5)
3.3.1 Assigning URIs to Entities
57(4)
3.4 Software for Working with Linked Data
61(12)
3.4.1 Ontology Authoring Environments
61(2)
3.4.2 Platforms and Environments for Working with (RDF) Data
63(5)
3.4.3 Software Libraries for Working with RDF
68(2)
References
70(3)
4 Creating Linked Data from Relational Databases
73(30)
4.1 Introduction
73(1)
4.2 Motivation-Benefits
74(3)
4.3 A Classification of Mapping Approaches
77(7)
4.4 Creating Ontology and Triples from a Relational Database
84(7)
4.4.1 Creating and Populating a Domain Ontology
86(3)
4.4.2 Mapping a database to an existing ontology
89(2)
4.5 Complete Example: Linked Data from the Scholarly/Cultural Heritage Domain
91(7)
4.5.1 Synchronous vs. Asynchronous Exports as LOD in Digital Repositories
94(1)
4.5.2 From DSpace to Europeana: A Use Case
94(4)
4.6 Future Outlook
98(5)
References
99(4)
5 Generating Linked Data in Real-time from Sensor Data Streams
103(24)
5.1 Introduction: Problem Framework
103(1)
5.2 Context-Awareness, Internet of Things, and Linked Data
104(1)
5.3 Fusion
105(2)
5.3.1 JDL Fusion Levels
106(1)
5.4 The Data Layer
107(8)
5.4.1 Modeling Context
108(2)
5.4.2 Annotation of Sensor Data
110(1)
5.4.3 Real-time vs. Near-real-time Synchronous vs. Asynchronous
111(1)
5.4.4 Data Synchronization and Timestamping
112(1)
5.4.5 Windowing
112(1)
5.4.6 The (Distributed) Data Storage Layer
113(2)
5.5 Rule-Based Stream Reasoning in Sensor Environments
115(3)
5.5.1 Rule-Based Reasoning in Jena
117(1)
5.5.2 Rule-Based Reasoning in Virtuoso
117(1)
5.6 Complete Example: Linked Data from a Multi-Sensor Fusion System Based on GSN
118(9)
5.6.1 The GSN Middleware
118(1)
5.6.2 Low Level Fusion
119(2)
5.6.3 A Sensor Fusion Architecture
121(2)
5.6.4 High Level Fusion Example
123(1)
References
124(3)
6 Conclusions: Summary and Outlook
127
6.1 Introduction
127(2)
6.2 Discussion
129(2)
6.3 Domain-Specific Benefits
131(1)
6.4 Open Research Challenges
132
References
133