| 000 | 10041nam a22008171i 4500 | ||
|---|---|---|---|
| 001 | 8374125 | ||
| 003 | IEEE | ||
| 005 | 20200413152930.0 | ||
| 006 | m eo d | ||
| 007 | cr cn |||m|||a | ||
| 008 | 180529s2018 caua foab 001 0 eng d | ||
| 020 |
_a9781681731285 _qebook |
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| 020 |
_z9781681733401 _qePub |
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| 020 |
_z9781681731278 _qprint |
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| 020 |
_z9781681732831 _qhardcover |
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| 024 | 7 |
_a10.2200/S00824ED1V01Y201801WBE017 _2doi |
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| 035 | _a(CaBNVSL)swl408349 | ||
| 035 | _a(OCoLC)1038017360 | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aTK5105.88815 _b.U823 2018 |
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| 082 | 0 | 4 |
_a006.332 _223 |
| 100 | 1 |
_aUschold, Michael, _eauthor. |
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| 245 | 1 | 0 |
_aDemystifying OWL for the enterprise / _cMichael Uschold. |
| 264 | 1 |
_a[San Rafael, California] : _bMorgan & Claypool, _c2018. |
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| 300 |
_a1 PDF (xxiv, 237 pages) : _billustrations. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 |
_aSynthesis lectures on the semantic web, _x2160-472X ; _v# 17 |
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| 538 | _aMode of access: World Wide Web. | ||
| 500 | _aPart of: Synthesis digital library of engineering and computer science. | ||
| 504 | _aIncludes bibliographical references (pages 215-218) and index. | ||
| 505 | 0 | _aPart 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 -- | |
| 505 | 8 | _aPart 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 -- | |
| 505 | 8 | _aPart 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 -- | |
| 505 | 8 | _aAppendices -- 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. | |
| 506 | _aAbstract freely available; full-text restricted to subscribers or individual document purchasers. | ||
| 510 | 0 | _aCompendex | |
| 510 | 0 | _aINSPEC | |
| 510 | 0 | _aGoogle scholar | |
| 510 | 0 | _aGoogle book search | |
| 520 | 3 | _aAfter a slow incubation period of nearly 15 years, a large and growing number of organizations now have one or more projects using the Semantic Web stack of technologies. The Web Ontology Language (OWL) is an essential ingredient in this stack, and the need for ontologists is increasing faster than the number and variety of available resources for learning OWL. This is especially true for the primary target audience for this book: modelers who want to build OWL ontologies for practical use in enterprise and government settings. The purpose of this book is to speed up the process of learning and mastering OWL. To that end, the focus is on the 30% of OWL that gets used 90% of the time. Others who may benefit from this book include technically oriented managers, semantic technology developers, undergraduate and post-graduate students, and finally, instructors looking for new ways to explain OWL. The book unfolds in a spiral manner, starting with the core ideas. Each subsequent cycle reinforces and expands on what has been learned in prior cycles and introduces new related ideas. Part 1 is a cook's tour of ontology and OWL, giving an informal overview of what things need to be said to build an ontology, followed by a detailed look at how to say them in OWL. This is illustrated using a healthcare example. Part 1 concludes with an explanation of some foundational ideas about meaning and semantics to prepare the reader for subsequent chapters. Part 2 goes into depth on properties and classes, which are the core of OWL. There are detailed descriptions of the main constructs that you are likely to need in every day modeling, including what inferences are sanctioned. Each is illustrated with real-world examples. Part 3 explains and illustrates how to put OWL into practice, using examples in healthcare, collateral, and financial transactions. A small ontology is described for each, along with some key inferences. Key limitations of OWL are identified, along with possible workarounds. The final chapter gives a variety of practical tips and guidelines to send the reader on their way. | |
| 530 | _aAlso available in print. | ||
| 588 | _aTitle from PDF title page (viewed on May 29, 2018). | ||
| 650 | 0 | _aOntologies (Information retrieval) | |
| 650 | 0 | _aSemantic Web. | |
| 650 | 0 | _aKnowledge acquisition (Expert systems) | |
| 653 | _aOWL | ||
| 653 | _aontology engineering | ||
| 653 | _adata modeling | ||
| 653 | _aconceptual modeling | ||
| 653 | _aSemantic Web | ||
| 653 | _aknowledge graph | ||
| 653 | _aenterprise ontology | ||
| 653 | _asemantic technology | ||
| 653 | _asemantics | ||
| 653 | _areuse | ||
| 653 | _amodularity | ||
| 653 | _ametadata | ||
| 653 | _aresource description framework (RDF) | ||
| 653 | _aRDF Schema | ||
| 653 | _atriples | ||
| 653 | _adescription logic | ||
| 653 | _aknowledge representation | ||
| 653 | _aweb ontology language | ||
| 655 | 0 | _aElectronic books. | |
| 776 | 0 | 8 |
_iPrint version: _z9781681731278 _z9781681732831 |
| 830 | 0 | _aSynthesis digital library of engineering and computer science. | |
| 830 | 0 |
_aSynthesis lectures on the semantic web ; _v# 17. _x2160-472X |
|
| 856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/servlet/opac?bknumber=8374125 |
| 999 |
_c562381 _d562381 |
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