Mastering structured data on the semantic web : from HTML5 microdata to linked open data /
Sikos, Leslie.author.
A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can "understand" such data better, which can be useful for task automation. The web sites that provide semantics (meaning) to software agents form the Semantic Web, the Artificial Intelligence extension of the World Wide Web. In contrast to the conventional Web (the "Web of Documents"), the Semantic Web includes the "Web of Data", which connects "things" (representing real-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical aspects and the theory behind the Semantic Web and how structured data, such as HTML5 Microdata and JSON-LD, can be used to improve your site's performance on next-generation Search Engine Result Pages and be displayed on Google Knowledge Panels. You will learn how to represent arbitrary fields of human knowledge in a machine-interpretable form using the Resource Description Framework (RDF), the cornerstone of the Semantic Web. You will see how to store and manipulate RDF data in purpose-built graph databases such as triplestores and quadstores, that are exploited in Internet marketing, social media, and data mining, in the form of Big Data applications such as the Google Knowledge Graph, Wikidata, or Facebook's Social Graph. With the constantly increasing user expectations in web services and applications, Semantic Web standards gain more popularity. This book will familiarize you with the leading controlled vocabularies and ontologies and explain how to represent your own concepts. After learning the principles of Linked Data, the five-star deployment scheme, and the Open Data concept, you will be able to create and interlink five-star Linked Open Data, and merge your RDF graphs to the LOD Cloud. The book also covers the most important tools for generating, storing, extracting, and visualizing RDF data, including, but not limited to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. You will learn to implement Apache Jena and Sesame in popular IDEs such as Eclipse and NetBeans, and use these APIs for rapid Semantic Web application development. Mastering Structured Data on the Semantic Web demonstrates how to represent and connect structured data to reach a wider audience, encourage data reuse, and provide content that can be automatically processed with full certainty. As a result, your web contents will be integral parts of the next revolution of the Web.
Description based upon print version of record.
Contents at a Glance; Contents; About the Author; About the Technical Reviewer; Preface; Chapter 1: Introduction to the Semantic Web;  The Semantic Web ;  Structured Data ;  Semantic Web Components;  Ontologies ; Ontology Engineering;  Inference ;  Semantic Web Features;  Free, Open Access Data Repositories ;  Adaptive Information ;  Unique Web Resource Identifiers ;  Summary;  References; Chapter 2: Knowledge Representation;  Vocabularies and Ontologies;  The schema.org Vocabulary Collection ;  General, Access, and Structural Metadata ;  Person Vocabularies ;  Book Vocabularies
PRISM: A Publishing Vocabulary  GoodRelations: An E-commerce Ontology ;  Publication Ontologies ;  DOAP: A Project Management Vocabulary ;  Licensing Vocabularies ;  Media Ontologies ;  Vocabularies for Online Communities ;  Knowledge Management Standards;  Resource Description Framework ( RDF) ;  Machine-Readable Annotations; Microformats; hCalendar and h-event;  hCard ;  rel=""license"" ;  rel=""nofollow"" ;  rel=""tag"" ;  Vote Links ;  XFN ;  XMDP ; Drafts and Future Microformats ;  RDFa ; RDFa DOM API; HTML5 Microdata; Global Microdata Attributes ; HTML5 Microdata DOM API ;  JSON-LD
JSON-LD DOM API GRDDL: XML Documents to RDF;  R2RML: Relational Databases to RDF ;  RDFS; Defining RDFS Classes ; Defining RDFS Subclasses ; Defining RDFS Instances ; Defining RDFS Properties ; Defining RDFS Domains and Ranges ;  Web Ontology Language (OWL); Description Logic ; O WL Variants ;  Syntaxes ;  Properties ;  Classes ;  Simple Knowledge Organization System (SKOS) ;  Rule Interchange Format ( RIF) ;  Reasoning ;  Parsers ;  Summary;  References; Chapter 3: Linked Open Data;  Linked Data Principles ;  The Five-Star Deployment Scheme for Linked Data ;  LOD Datasets ;  RDF Crawling
RDF Dumps  SPARQL Endpoints ;  Frequently Used Linked Datasets;  DBpedi a ;  Wikidata ;  GeoNames ;  LinkedGeoData ;  YAG O ;  LOD Dataset Collections ;  The LOD Cloud Diagram ;  Creating LOD Datasets;  RDF Structure ;  Licensing ;  RDF Statements ;  Interlinking ;  Registering Your Dataset ;  Linked Data Visualization ;  Summary;  References; Chapter 4: Semantic Web Development Tools;  Advanced Text Editors ;  Semantic Annotators and Converters;  RDFa Play ;  RDFa 1.1 Distiller and Parser ;  RDF Distiller ;  DBpedia Spotlight ;  Google Structured Data Testing Tool ;  RDFizers
Apache Any23  General Architecture for Text Engineering ( GATE) ;  OpenRefine ;  Ontology Editors;  Protégé ;  SemanticWorks ;  TopBraid Composer ;  Apache Stanbol ;  Fluent Editor ;  Ontology Analysis Tools;  ZOOMA ;  Semantic Measures Library ;  Reasoners;  HermiT ;  Pellet ;  FaCT++ ;  RACER ;  Application Development Frameworks;  Jena ;  Sesame ;  Integrated Development Environments;  Eclipse ;  Set Up Apache Jena in Eclipse;  Set Up Sesame in Eclipse ;  NetBean s ; Setup Apache Jena in NetBeans;  CubicWeb ;  Linked Data Software;  Sindice ;  Apache Marmott a ;  sameAs.org
Callimachus
Includes bibliographical references at the end of each chapters and index.
A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can "understand" such data better, which can be useful for task automation. The web sites that provide semantics (meaning) to software agents form the Semantic Web, the Artificial Intelligence extension of the World Wide Web. In contrast to the conventional Web (the "Web of Documents"), the Semantic Web includes the "Web of Data", which connects "things" (representing real-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical aspects and the theory behind the Semantic Web and how structured data, such as HTML5 Microdata and JSON-LD, can be used to improve your site's performance on next-generation Search Engine Result Pages and be displayed on Google Knowledge Panels. You will learn how to represent arbitrary fields of human knowledge in a machine-interpretable form using the Resource Description Framework (RDF), the cornerstone of the Semantic Web. You will see how to store and manipulate RDF data in purpose-built graph databases such as triplestores and quadstores, that are exploited in Internet marketing, social media, and data mining, in the form of Big Data applications such as the Google Knowledge Graph, Wikidata, or Facebook's Social Graph. With the constantly increasing user expectations in web services and applications, Semantic Web standards gain more popularity. This book will familiarize you with the leading controlled vocabularies and ontologies and explain how to represent your own concepts. After learning the principles of Linked Data, the five-star deployment scheme, and the Open Data concept, you will be able to create and interlink five-star Linked Open Data, and merge your RDF graphs to the LOD Cloud. The book also covers the most important tools for generating, storing, extracting, and visualizing RDF data, including, but not limited to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. You will learn to implement Apache Jena and Sesame in popular IDEs such as Eclipse and NetBeans, and use these APIs for rapid Semantic Web application development. Mastering Structured Data on the Semantic Web demonstrates how to represent and connect structured data to reach a wider audience, encourage data reuse, and provide content that can be automatically processed with full certainty. As a result, your web contents will be integral parts of the next revolution of the Web.
Computer programming.
Data structures (Computer science).
Web Development.
Data Structures and Information Theory.