By Leslie F. Sikos

An immense challenge of traditional websites is their unorganized and remoted contents, that is created regularly for human intake. This challenge might be addressed via organizing and publishing info, utilizing robust codecs that upload constitution and aspiring to the content material of web content and hyperlink similar facts to each other. desktops can "understand" such facts greater, which might be important for job automation. the net websites that supply semantics (meaning) to software program brokers shape the Semantic net, the substitute Intelligence extension of the realm vast internet. not like the traditional net (the "Web of Documents"), the Semantic internet comprises the "Web of Data", which connects "things" (representing real-world people and items) instead of records meaningless to pcs. getting to know based information at the Semantic net explains the sensible points and the idea in the back of the Semantic net and the way established info, akin to HTML5 Microdata and JSON-LD, can be utilized to enhance your site’s functionality on next-generation seek Engine consequence Pages and be displayed on Google wisdom Panels. you are going to how one can signify arbitrary fields of human wisdom in a machine-interpretable shape utilizing the source Description Framework (RDF), the cornerstone of the Semantic internet. you can find how you can shop and manage RDF info in purpose-built graph databases reminiscent of triplestores and quadstores, which are exploited in online marketing, social media, and information mining, within the type of mammoth information functions akin to the Google wisdom Graph, Wikidata, or Facebook’s Social Graph.

With the consistently expanding person expectancies in net providers and functions, Semantic internet criteria achieve extra reputation. This publication will familiarize you with the best managed vocabularies and ontologies and clarify tips on how to characterize your personal innovations. After studying the rules of associated info, the five-star deployment scheme, and the Open info thought, it is possible for you to to create and interlink five-star associated Open info, and merge your RDF graphs to the LOD Cloud. The ebook additionally covers crucial instruments for producing, storing, extracting, and visualizing RDF info, together with, yet now not restricted to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. you are going to learn how to enforce Apache Jena and Sesame in well known IDEs equivalent to Eclipse and NetBeans, and use those APIs for fast Semantic net program improvement. learning dependent facts at the Semantic internet demonstrates easy methods to characterize and attach based info to arrive a much wider viewers, inspire facts reuse, and supply content material that may be instantly processed with complete walk in the park. therefore, your net contents could be crucial elements of the subsequent revolution of the Web.

What you’ll learn

expand your markup with machine-readable annotations and get your info to the Google wisdom Graph
signify real-world items and folks with machine-interpretable code
improve Semantic internet functions in Java
Reuse and interlink dependent information and create LOD datasets

Who this e-book is for

The e-book is meant for net builders and website positioning specialists who are looking to research cutting-edge SEO equipment utilizing machine-readable annotations and machine-interpretable associated facts definitions. The e-book also will gain researchers attracted to computerized wisdom discovery. As a textbook on Semantic internet criteria powered by way of graph concept and mathematical common sense, the booklet may be used as a reference paintings for computing device technological know-how graduates and Semantic net researchers.
Table of Contents

1. advent to the Semantic Web

2. wisdom Representation

3. associated Open Data

4. Semantic internet improvement Tools

5. Semantic internet Services

6. Graph Databases

7. Querying

8. gigantic information Applications

9. Use circumstances

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Example text

10 Listing 2-60 shows an example. Listing 2-60. A Class Identifier in OWL In OWL Lite and OWL DL. In OWL-Full they are equivalent. 10 51 Chapter 2 ■ Knowledge Representation 2. Set of individuals (instances of a class) defined by the owl:oneOf property. For example, the class of smartphones can be declared in the RDF/XML syntax, with the RDF construct rdf:parseType="Collection", as shown in Listing 2-61. Listing 2-61. Declaring Class Instances in OWL 3.

RIF has a mapping to RDF. Reasoning Description logic-based ontologies are crucial in describing the meaning of web resources and can leverage powerful description logic reasoning tools to facilitate machine-processability of semantic web sites. Reasoning derives facts that are not expressed explicitly in machine-readable ontologies or knowledge bases. Description logic reasoners implement the analytic tableau method (truth tree) for semantic reasoning, which is the most popular proof procedure for formulas of first-order predicate logic.

The address identifier provides the relation between the two tables (Figure 2-6). Figure 2-6. RDB input tables The R2RML direct mapping of this example would create a People class with a Leslie entity with ID 5, an Addresses class with the city and state details of the Leslie entity, and a link between the Leslie entity and the associated address (Listing 2-42). Listing 2-42. com/DB/> . org/2001/XMLSchema#> . rdf:type . 5 . "Leslie" .

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