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| Genre/Form: | Electronic books |
|---|---|
| Additional Physical Format: | Print version: |
| Material Type: | Document, Internet resource |
| Document Type: | Internet Resource, Computer File |
| All Authors / Contributors: |
Michael Uschold |
| ISBN: | 9781681731285 1681731282 9781681733401 1681733404 |
| OCLC Number: | 1038017360 |
| Description: | 1 online resource (xxiv, 237 pages) : illustrations |
| Contents: | Part 1. Introducing OWL -- 1. Getting started: what do we need to say? -- 1.1 What is an ontology? What is OWL? -- 1.2 In the beginning there are things -- 1.3 Kinds of things vs. individual things -- 1.4 No thing is an island -- 1.4.1 Healthcare -- 1.4.2 Finance -- 1.4.3 Corporate registrations -- 1.5 Things can have a variety of attributes -- 1.6 More general things and more specific things -- 1.7 Drawing conclusions -- 1.8 Data and metadata -- 1.9 Summary learning -- 2. How do we say it in OWL? -- 2.1 Introduction -- 2.2 Saying things -- 2.2.1 An ontology is a set of triples -- 2.2.2 Namespaces, resource identifiers, and OWL syntax -- 2.2.3 Summary: informal to formal -- 2.2.4 Notational conventions -- 2.3 A simple ontology in healthcare -- 2.3.1 Healthcare data -- 2.3.2 Healthcare metadata -- 2.3.3 Individuals and their types -- 2.3.4 Richer semantics and automatic categorization -- 2.3.5 Other ways to specify meaning -- 2.3.6 Pause and reflect -- 2.4 Summary of key OWL concepts and assertions -- 2.4.1 Vocabularies and namespaces -- 2.4.2 Individuals and classes -- 2.4.3 Properties -- 2.4.4 Class expressions and restrictions -- 2.4.5 Drawing conclusions -- 2.5 Summary learning -- 3. Fundamentals: meaning, semantics, and sets -- 3.1 Logic -- 3.1.1 Reasoning and arguments -- 3.1.2 Formal semantics and sets -- 3.1.3 The open world -- 3.1.4 Resource identifiers -- 3.1.5 Literals and datatypes -- 3.1.6 Metaclasses -- 3.1.7 Expressions -- 3.1.8 Meaning, semantics, and ambiguity -- 3.1.9 Concepts vs. terms -- 3.1.10 The world of triples -- 3.1.11 Reuse and modularity -- 3.1.12 Triple stores, querying, and SPARQL -- 3.1.13 Summary learning -- 3.2 Summary for part 1 Part 2. Going into depth: properties and classes -- 4. Properties -- 4.1 Properties, relationships, and sets -- 4.2 Properties are first-class objects -- 4.3 Property hierarchies -- 4.4 Domain and range -- 4.4.1 Use domain and range with care -- 4.5 Inverse properties and property chains -- 4.5.1 Inverse properties -- 4.5.2 Property chains -- 4.6 Property characteristics -- 4.6.1 Functional properties -- 4.6.2 Transitive properties -- 4.6.3 Symmetric and asymmetric properties -- 4.7 Property characteristics of subproperties and inverse properties -- 4.7.1 Subproperties -- 4.7.2 Inverse properties -- 4.8 Data properties -- 4.8.1 Data vs. object properties -- 4.8.2 When to use data properties -- 4.9 Disjointness and equivalence -- 4.10 Annotation properties -- 4.11 Summary learning -- 5. Classes -- 5.1 Review: classes and sets -- 5.2 Class relationships -- 5.2.1 Subclass -- 5.2.2 Class equivalence -- 5.2.3 Disjoint classes -- 5.3 Class expressions -- 5.3.1 Anonymous classes and blank nodes -- 5.3.2 Boolean expressions -- 5.3.3 Enumeration -- 5.3.4 Property restrictions -- 5.3.5 Summary: class expressions -- 5.4 Property restrictions -- 5.4.1 Usage scenarios -- 5.4.2 Anatomy of a property restriction -- 5.4.3 Existential: someValuesFrom -- 5.4.4 Universal: allValuesFrom -- 5.4.5 Minimum cardinality -- 5.4.6 Maximum cardinality -- 5.4.7 Exact cardinality -- 5.4.8 Individual value: hasValue -- 5.4.9 Data property restrictions -- 5.4.10 Summary: property restrictions -- 5.5 Summary learning -- 5.6 Conclusion for Part 2 Part 3. Using OWL in practice -- 6. More examples -- 6.1 Patient visit -- 6.2 Collateral -- 6.3 Internal vs. external transactions -- 6.4 Inference -- 6.4.1 Patient visit -- 6.4.2 Inference with partial information -- 6.4.3 Security agreement and collateral -- 6.4.4 Internal organizations and transactions -- 6.4.5 Classification inference -- 6.5 Summary learning -- 7. OWL limitations -- 7.1 Metaclasses -- 7.2 The object of a triple -- 7.3 N-ary relations -- 7.4 Rules -- 7.5 Dates and times -- 7.6 Cardinality restrictions with transitive properties or property chains -- 7.7 Inference at scale -- 7.8 Summary learning -- 8. Go forth and ontologize -- 8.1 Modeling principles and tools -- 8.1.1 Conceptual and operational -- 8.1.2 Concepts, terms, and naming conventions -- 8.1.3 Modeling choice: data or object property? -- 8.1.4 Modeling choice: class or property? -- 8.1.5 Modeling choice: class or individual? -- 8.1.6 Modularity for reusability -- 8.1.7 Ontology editors and inference engines -- 8.2 modeling patterns -- 8.2.1 Genus differentia -- 8.2.2 Orphan classes and high-level disjoints -- 8.2.3 Upper ontologies -- 8.2.4 N-ary relations -- 8.2.5 Buckets, buckets everywhere -- 8.2.6 Roles -- 8.3 Common pitfalls -- 8.3.1 Reading too much into IRIs and labels -- 8.3.2 Unique name assumption -- 8.3.3 Namespace proliferation -- 8.3.4 Domain and range -- 8.3.5 Less is more -- 8.4 Less frequently used OWL constructs -- 8.4.1 Pairwise disjoint and disjoint union -- 8.4.2 Datatypes -- 8.4.3 Different individuals -- 8.4.4 Same individuals -- 8.4.5 Deprecation -- 8.5 The open world revisited -- 8.6 Summary learning -- 8.7 Final remarks Appendices -- A.1 Acronyms & abbreviations -- A.2 e6Tools visual OWL syntax -- A.3 Recommended resources for further learning -- A.4 Answers to exercises -- A.4.1 Chapter 1 -- A.4.2 Chapter 2 -- A.4.4 Chapter 4 -- A.4.5 Chapter 5 -- A.4.6 Chapter 6 -- Author biography -- Index. |
| Series Title: | Synthesis lectures on the semantic web, theory and technology, #17. |
| Responsibility: | Michael Uschold. |
| More information: |
Abstract:
The purpose of this book is to speed up the process of learning and mastering Web Ontology Language (OWL). The focus is on the 30% of OWL that gets used 90% of the time. The book unfolds in a spiral manner, starting with the core ideas. Each subsequent cycle expands on what has been learned in prior cycles and introduces related ideas.
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Related Subjects:(23)
- OWL (Web ontology language)
- Ontologies (Information retrieval)
- Semantic Web.
- Knowledge acquisition (Expert systems)
- COMPUTERS -- General.
- OWL
- ontology engineering
- data modeling
- conceptual modeling
- Semantic Web
- knowledge graph
- enterprise ontology
- semantic technology
- semantics
- reuse
- modularity
- metadata
- resource description framework (RDF)
- RDF Schema
- triples
- description logic
- knowledge representation
- web ontology language
