Semantic Web for the Working Ontologist book cover

Semantic Web for the Working Ontologist

Effective Modeling in RDFS and OWL

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications.

Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content.

New in this edition:

  • Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below
  • Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more


Programmers, web developers, and application developers; technologists and graduate students in computer science

Paperback, 384 Pages

Published: May 2011

Imprint: Morgan Kaufmann

ISBN: 978-0-12-385965-5


  • "Overall, this book provides a thorough and cogent introduction to the semantic Web. Giving just enough philosophical background, the authors focus on the practical aspects of constructing data stores and applications. This blend of philosophy and practical descriptions leads the reader to anticipate how the standards of the semantic Web should work before the standards are described. As a result, the reader is likely to feel that the semantic Web works just as it should."--Computing Reviews

    "Allemang, a scientist at a company that consults, trains, and provides products for the Semantic Web, and Hendler (computer and cognitive science, Rensselaer Polytechnic Institute) explain how web developers who are practitioners in another field, such as health care, finance, engineering, national intelligence, and enterprise architecture, can model data to fit the requirements of the Semantic Web. They detail how to construct semantic models, with a focus on the use of RDF (Resource Description Framework), RDFS (RDF schema), and OWL (Web Ontology Language) to accomplish specific tasks and model data and domains. This edition has been updated to incorporate new technologies such as SPARQL (SPARQL Protocol And RDF Query Language), OWL 2.0, and SKOS (Simple Knowledge Organization System). They include examples of Quantities, Units, Dimensions, and Types (QUDT) and The Open Biological and Biomedical Ontologies (OBO), as well as examples of how to use the Semantic Web to solve common modeling problems and a FAQ section on challenges."--SciTech Book News

    "Overall, this is an easy-to-follow guide to the basic concepts related to building semantic Web ontologies. The book flows well from chapter to chapter, and the many examples illustrate the different topics. For beginners, it’s an excellent introduction to the subject, which is exactly what the authors intended…"--Computing


  • 1 What Is the Semantic Web?

    • What Is a Web?
    • Smart Web, Dumb Web
    • Smart Web Applications
    • A Connected Web Is a Smarter Web
    • Semantic Data
    • A Distributed Web of Data
    • Features of a Semantic Web
    • What about the Round-Worlders?
    • To Each Their Own
    • There’s Always One More
    • Summary
    • Fundamental Concepts


    2 Semantic Modeling

    • Modeling for Human Communication
    • Explanation and Prediction
    • Mediating Variability
    • Variation and Classes
    • Variation and Layers
    • Expressivity in Modeling
    • Summary
    • Fundamental Concepts


    3 RDF-The Basis of the Semantic Web

    • Distributing Data Across the Web
    • Merging Data from Multiple Sources
    • Namespaces, URIs, and Identity
    • Expressing URIs in Print
    • Standard Namespaces
    • Identifiers in the RDF Namespace
    • Challenge: RDF and Tabular Data
    • Higher-Order Relationships
    • Alternatives for Serialization
    • N-Triples
    • Turtle Notation
    • RDF/XML
    • RDF in HTML - RDFa Blank Nodes
    • Ordered Information in RDF
    • Summary
    • Fundamental Concepts

    4 SPARQL - The Query Language for RDF

    • Tell-and-Ask Systems
    • Common Tell-and-Ask Infrastructure: Spreadsheet
    • Advanced Tell-and-Ask Infrastructure: Relational Database
    • RDF as a Tell-and-Ask System
    • SPARQL - Query Language for RDF
    • Naming Variables in SPARQL
    • Query Structure vs. Data Structure
    • Ordering of triples in SPARQL Queries
    • Querying for Properties and Schema
    • Variables, Bindings and Filters
    • Optional Matches
    • Negation
    • CONSTRUCT Queries in SPARQL
    • Using SPARQL as a Rule Language - SPARQL Rules
    • Challenge: Using SPARQL to Transform Data
    • Advanced Features of SPARQL
    • Aggregates
    • UNION
    • Assignments
    • Subqueries
    • Challenge: Using SPARQL to Integrate
    • Federating SPARQL queries
    • Named Graphs
    • SPARQL Endpoints


    5 Semantic Web Application Architecture

    • RDF Parser/Serializer
    • Other Data Sources-Converters and Scrapers
    • RDF Store
    • RDF Data Standards and Interoperability of RDF Stores
    • RDF Query Engines and SPARQL
    • Comparison to Relational Queries
    • Application Code
    • RDF-Backed Web Portals
    • Data Federation
    • Summary
    • Fundamental Concepts


    6 RDF and Inferencing

    • Inference in the Semantic Web
    • Virtues of Inference-Based Semantics
    • Where are the Smarts?
    • Asserted Triples versus Inferred Triples
    • When Does Inferencing Happen?
    • Inferencing as Glue
    • Summary
    • Fundamental Concepts


    7 RDF Schema

    • Schema Languages and Their Functions
    • What Does It Mean? Semantics as Inference
    • The RDF Schema Language
    • Relationship Propagation through rdfs:subPropertyOf
    • Typing Data by Usage-rdfs:domain and rdfs:range
    • Combination of Domain and Range with rdfs:subClassOf
    • RDFS Modeling Combinations and Patterns
    • Set Intersection
    • Property Intersection
    • Set Union
    • Property Union
    • Property Transfer
    • Challenges
    • Term Reconciliation
    • Instance-Level Data Integration
    • Readable Labels with rdfs:label
    • Data Typing Based on Use
    • Filtering Undefined Data
    • RDFS and Knowledge Discovery
    • Modeling with Domains and Ranges
    • Multiple Domains/Ranges
    • Nonmodeling Properties in RDFS
    • Cross-Referencing Files: rdfs:seeAlso
    • Organizing Vocabularies: rdfs:isDefinedBy
    • Model Documentation: rdfs:comment
    • Summary
    • Fundamental Concepts


    8 RDFS-Plus

    • Inverse
    • Challenge: Integrating Data that Do Not Want to Be Integrated
    • Challenge: Using the Modeling Language to Extend the Modeling Language
    • Challenge: The Marriage of Shakespeare
    • Symmetric Properties
    • Using OWL to Extend OWL
    • Transitivity
    • Challenge: Relating Parents to Ancestors
    • Challenge: Layers of Relationships
    • Managing Networks of Dependencies
    • Equivalence
    • Equivalent Classes
    • Equivalent Properties
    • Same Individuals
    • Challenge: Merging Data from Different Databases
    • Computing Sameness-Functional Properties
    • Functional Properties
    • Inverse Functional Properties
    • Combining Functional and Inverse Functional Properties
    • A Few More Constructs
    • Summary
    • Fundamental Concepts

    9 SKOS - the Simple Knowledge Organization System

    • Semantic Relations in SKOS
    • Meaning of Semantic Relations
    • Special Purpose Inference
    • Published Subject Indicators
    • SKOS Matching Vocabulary
    • Modeling Patterns in SKOS
    • SKOS in Action: AGROVOC
    • SKOS in Action: Federal Enterprise Architecture
    • SKOS in Action: Library of Congress Subject Headings


    10 Ontologies in the Wild

    • RDF and Linked Open Data
    • Liked Open Data Resources
    • SPARQL Endpoints
    • Using SPARQL to Access and Explore Open Data
    • Open Data and Government
    • Facebook and the Open Graph Protocol
    • Markup of HTML Pages
    • The fb: namespace
    • Mapping fb: to other namespaces with RDFS
    • FOAF (Friend of a Friend)
    • People and Agents
    • Names in FOAF
    • Nicknames and Online Names
    • Online Persona
    • Groups of People
    • Things People Make and Do
    • Identity in FOAF
    • It’s Not What You Know, It’s Who You Know
    • Summary
    • Fundamental Concepts

    11 Basic OWL

    • Restrictions
    • Example: Questions and Answers
    • Adding "Restrictions"
    • Kinds of Restrictions
    • Challenge Problems
    • Challenge: Local Restriction of Ranges
    • Challenge: Filtering Data Based on Explicit Type
    • Challenge: Relationship Transfer in SKOS
    • Relationship Transfer in FOAF
    • Alternative Descriptions of Restrictions
    • Summary
    • Fundamental Concepts

    12 Counting and Sets in OWL

    • Unions and Intersections
    • Closing the World
    • Enumerating Sets with owl:oneOf
    • Differentiating Individuals with owl:differentFrom
    • Differentiating Multiple Individuals
    • Cardinality
    • Small Cardinality Limits
    • Set Complement
    • Disjoint Sets
    • Prerequisites Revisited
    • No Prerequisites
    • Counting Prerequisites
    • Guarantees of Existence
    • Contradictions
    • Unsatisfiable Classes
    • Propagation of Unsatisfiable Classes
    • Inferring Class Relationships
    • Reasoning with Individuals and with Classes
    • Summary
    • Fundamental Concepts


    13 Ontologies in the Wild (reprise)

    • QUDT (Quantities, Units, Dimensions and Types)
    • Basic distinctions - Quantities, Units and Dimensions
    • Dimensions and Conversions
    • Local Restrictions of Ranges
    • Converting units with SPARQL
    • GoodRelations - Ontology for eCommerce
    • Modeling and eCommerce
    • Structure Search and Search Optimization
    • GoodRelations and HTML
    • GoodRelations Axioms and Rules
    • Linking GoodRelations to other vocabularies
    • GoodRelations Results and Impact
    • The Open Biological and Biomedical Ontologies (OBO Foundry)
    • Requirements of NCI, CHEBI, CHEMBL, etc.
    • Upper-Level Classes
    • Describing Classes in OBO
    • Class-Level Inferencing in OBO
    • Instance-Level Inferencing in OBO
    • Summary
    • Fundamental Concepts

    14 Good and Bad Modeling Practices

    • Getting Started
    • Know What You Want
    • Inference: Say what you mean, and mean what you say
    • Modeling for Reuse
    • Insightful Names versus Wishful Names
    • Modeling Classes and Individuals
    • Model Testing
    • Common Modeling Errors
    • Rampant Classism (Antipattern)
    • Exclusivity (Antipattern)
    • Objectification (Antipattern)
    • Managing Identifiers for Classes (Antipattern)
    • Creeping Conceptualization (Antipattern)
    • Summary
    • Fundamental Concepts

    15 OWL Levels and Logic

    • OWL Dialects and Modeling Philosophy
    • OWL Full versus OWL DL
    • OWL 2.0
    • Metamodeling
    • Multipart Properties
    • Qualified Cardinality
    • Multiple Inverse Functional Properties
    • OWL Profiles
    • Climbing the ladder: SPARQL, OWL, Rules
    • Fundamental Concepts

    16 Conclusions

    APPENDIX Frequently Asked Questions


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