Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL
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Table of contents
- Cover
- Contentsvii
- Prefacexiii
- About the Authorsxvii
- Chapter 1: What Is the Semantic Web?1
- What Is a Web?1
- Smart Web, Dumb Web2
- Smart Web Applications3
- A Connected Web Is a Smarter Web4
- Semantic Data5
- A Distributed Web of Data6
- Features of a Semantic Web7
- What about the Round-Worlders?9
- To Each Their Own10
- There's Always One More11
- Summary12
- Fundamental Concepts13
- Chapter 2: Semantic Modeling15
- Modeling for Human Communication17
- Explanation and Prediction19
- Mediating Variability21
- Variation and Classes22
- Variation and Layers23
- Expressivity in Modeling26
- Summary28
- Fundamental Concepts29
- Chapter 3: RDF-The Basis of the Semantic Web31
- Distributing Data Across the Web32
- Merging Data from Multiple Sources36
- Namespaces, URIs, and Identity37
- Expressing URIs in Print40
- Standard Namespaces43
- Identifiers in the RDF Namespace44
- Challenge: RDF and Tabular Data45
- Higher-Order Relationships49
- Alternatives for Serialization51
- N-Triples51
- Notation 3 RDF (N3)52
- RDF/XML53
- Blank Nodes54
- Ordered Information in RDF56
- Summary56
- Fundamental Concepts57
- Chapter 4: Semantic Web Application Architecture59
- RDF Parser/Serializer60
- Other Data Sources-Converters and Scrapers61
- RDF Store64
- RDF Data Standards and Interoperability of RDF Stores66
- RDF Query Engines and SPARQL66
- Comparison to Relational Queries72
- Application Code73
- RDF-Backed Web Portals75
- Data Federation75
- Summary76
- Fundamental Concepts77
- Chapter 5: RDF and Inferencing79
- Inference in the Semantic Web80
- Virtues of Inference-Based Semantics82
- Where Are the Smarts?83
- Asserted Triples versus Inferred Triples85
- When Does Inferencing Happen?87
- Inferencing as Glue88
- Summary89
- Fundamental Concepts90
- Chapter 6: RDF Schema91
- Schema Languages and their Functions91
- What Does it Mean? Semantics as Inference93
- The RDF Schema Language95
- Relationship Propagation through rdfs:subPropertyOf95
- Typing Data by Usage-rdfs:domain and rdfs:range98
- Combination of Domain and Range with rdfs:subClassOf99
- RDFS Modeling Combinations and Patterns102
- Set Intersection102
- Property Intersection104
- Set Union105
- Property Union106
- Property Transfer106
- Challenges108
- Term Reconciliation108
- Instance-Level Data Integration110
- Readable Labels with rdfs:label110
- Data Typing Based on Use111
- Filtering Undefined Data115
- RDFS and Knowledge Discovery115
- Modeling with Domains and Ranges116
- Multiple Domains/Ranges116
- Nonmodeling Properties in RDFS120
- Cross-Referencing Files: rdfs:seeAlso120
- Organizing Vocabularies: rdfs:isDefinedBy121
- Model Documentation: rdfs:comment121
- Summary121
- Fundamental Concepts122
- Chapter 7: RDFS-Plus123
- Inverse124
- Challenge: Integrating Data that Do Not Want to Be Integrated125
- Challenge: Using the Modeling Language to Extend the Modeling Language127
- Challenge: The Marriage of Shakespeare129
- Symmetric Properties129
- Using OWL to Extend OWL130
- Transitivity131
- Challenge: Relating Parents to Ancestors132
- Challenge: Layers of Relationships133
- Managing Networks of Dependencies134
- Equivalence139
- Equivalent Classes141
- Equivalent Properties142
- Same Individuals143
- Challenge: Merging Data from Different Databases146
- Computing Sameness-Functional Properties149
- Functional Properties150
- Inverse Functional Properties151
- Combining Functional and Inverse Functional Properties154
- A Few More Constructs155
- Summary156
- Fundamental Concepts157
- Chapter 8: Using RDFS-Plus in the Wild159
- SKOS159
- Semantic Relations in SKOS163
- Meaning of Semantic Relations165
- Special Purpose Inference166
- Published Subject Indicators168
- SKOS in Action168
- FOAF169
- People and Agents170
- Names in FOAF171
- Nicknames and Online Names171
- Online Persona172
- Groups of People173
- Things People Make and Do174
- Identity in FOAF175
- It's Not What You Know, It's Who You Know176
- Summary177
- Fundamental Concepts178
- Chapter 9: Basic OWL179
- Restrictions179
- Example: Questions and Answers180
- Adding "Restrictions"183
- Kinds of Restrictions184
- Challenge Problems196
- Challenge: Local Restriction of Ranges196
- Challenge: Filtering Data Based on Explicit Type198
- Challenge: Relationship Transfer in SKOS202
- Relationship Transfer in FOAF204
- Alternative Descriptions of Restrictions209
- Summary210
- Fundamental Concepts211
- Chapter 10: Counting and Sets in OWL213
- Unions and Intersections214
- Closing the World216
- Enumerating Sets with owl:oneOf216
- Differentiating Individuals with owl:differentFrom218
- Differentiating Multiple Individuals219
- Cardinality222
- Small Cardinality Limits225
- Set Complement226
- Disjoint Sets228
- Prerequisites Revisited231
- No Prerequisites232
- Counting Prerequisites233
- Guarantees of Existence234
- Contradictions235
- Unsatisfiable Classes237
- Propagation of Unsatisfiable Classes237
- Inferring Class Relationships238
- Reasoning with Individuals and with Classes243
- Summary244
- Fundamental Concepts245
- Chapter 11: Using OWL in the Wild247
- The Federal Enterprise Architecture Reference Model Ontology248
- Reference Models and Composability249
- Resolving Ambiguity in the Model: Sets Versus Individuals251
- Constraints Between Models253
- OWL and Composition255
- owl:Ontology255
- owl:imports256
- Advantages of the Modeling Approach257
- The National Cancer Institute Ontology258
- Requirements of the NCI Ontology259
- Upper-Level Classes261
- Describing Classes in the NCI Ontology266
- Instance-Level Inferencing in the NCI Ontology267
- Summary269
- Fundamental Concepts270
- Chapter 12: Good and Bad Modeling Practices271
- Getting Started271
- Know What You Want272
- Inference Is Key273
- Modeling for Reuse274
- Insightful Names Versus Wishful Names274
- Keeping Track of Classes and Individuals275
- Model Testing277
- Common Modeling Errors277
- Rampant Classism (Antipattern)277
- Exclusivity (Antipattern)282
- Objectification (Antipattern)285
- Managing Identifiers for Classes (Antipattern)288
- Creeping Conceptualization (Antipattern)289
- Summary290
- Fundamental Concepts291
- Chapter 13: OWL Levels and Logic293
- OWL Dialects and Modeling Philosophy294
- Provable Models294
- Executable Models296
- OWL Full versus OWL DL297
- Class/Individual Separation298
- InverseFunctional Datatypes298
- OWL Lite299
- Other Subsets of OWL299
- Beyond OWL 1.0300
- Metamodeling300
- Multipart Properties301
- Qualified Cardinality302
- Multiple Inverse Functional Properties302
- Rules303
- Summary304
- Fundamental Concepts304
- Chapter 14: Conclusions307
- Appendix: Frequently Asked Questions313
- Further Reading317
- Index321
The promise of the Semantic Web to provide a universal medium to exchange data information and knowledge has been well publicized. There are many sources too for basic information on the extensions to the WWW that permit content to be expressed in natural language yet used by software agents to easily find, share and integrate information. Until now individuals engaged in creating ontologies-- formal descriptions of the concepts, terms, and relationships within a given knowledge domain-- have had no sources beyond the technical standards documents.
Semantic Web for the Working Ontologist transforms this information into the practical knowledge that programmers and subject domain experts need. Authors Allemang and Hendler begin with solutions to the basic problems, but don’t stop there: they demonstrate how to develop your own solutions to problems of increasing complexity and ensure that your skills will keep pace with the continued evolution of the Semantic Web.
• Provides practical information for all programmers and subject matter experts engaged in modeling data to fit the requirements of the Semantic Web.
• De-emphasizes algorithms and proofs, focusing instead on real-world problems, creative solutions, and highly illustrative examples.
• Presents detailed, ready-to-apply “recipes for use in many specific situations.
• Shows how to create new recipes from RDF, RDFS, and OWL constructs.
Semantic Web for the Working Ontologist transforms this information into the practical knowledge that programmers and subject domain experts need. Authors Allemang and Hendler begin with solutions to the basic problems, but don’t stop there: they demonstrate how to develop your own solutions to problems of increasing complexity and ensure that your skills will keep pace with the continued evolution of the Semantic Web.
• Provides practical information for all programmers and subject matter experts engaged in modeling data to fit the requirements of the Semantic Web.
• De-emphasizes algorithms and proofs, focusing instead on real-world problems, creative solutions, and highly illustrative examples.
• Presents detailed, ready-to-apply “recipes for use in many specific situations.
• Shows how to create new recipes from RDF, RDFS, and OWL constructs.