The Semantic Web : semantics for data and services on the Web

A decade ago Tim Berners-Lee proposed an extraordinary vision: despite the p- nomenal success of the Web, it would not, and could not, reach its full potential unless it became a place where automated processes could participate as well as people. This meant the publication of documents and data to the web in such a way that they could be interpreted, integrated, aggregated and queried to reveal new connections and answer questions, rather than just browsed and searched. Many scoffed at this idea, interpreting the early emphasis on language design and reas- ing as AI in new clothes. This missed the point. The Grand Challenge of the Semantic Web is one that needs not only the information structure of ontologies, metadata, and data, but also the computational infrastructure of Web Services, P2P and Grid distributed computing and workflows. Consequently, it is a truly who- system and multi-disciplinary effort. This is also an initiative that has to be put into practice. That means a pragmatic approach to standards, tools, mechanisms and methodologies, and real, challenging examples. It would seem self-evident that the Semantic Web should be able to make a major contribution to clinical information discovery. Scientific commu- ties are ideal incubators: knowledge-driven, fragmented, diverse, a range of str- tured and unstructured resources with many disconnected suppliers and consumers of knowledge. Moreover, the clinicians and biosciences have embraced the notions of annotation and classification using ontologies for centuries, and have dema- ing requirements for trust, security, fidelity and expressivity.

• Part I Preliminaries p. 1
• 1 Introduction p. 3
• 1.1 Motivation: Why Semantic Web? p. 4
• 1.2 A Framework for Semantic Web p. 5
• 1.3 Use Case: Translational Medicine Clinical Vignette p. 7
• 1.4 Scope and Organization p. 9
• 2 Use Case and Functional Requirements p. 11
• 2.1 Detailed Clinical Use Case p. 12
• 2.2 Stakeholders and Information Needs p. 13
• 2.3 Conceptual Architecture p. 15
• 2.4 Functional Requirements p. 17
• 2.5 Research Issues p. 18
• 2.6 Summary p. 19
• Part II Information Aspects of the Semantic Web p. 21
• 3 Semantic Web Content p. 23
• 3.1 Nature of Web Content p. 23
• 3.2 Nature of Semantic Web Content p. 24
• 3.3 Metadata p. 25
• 3.3.1 Metadata Usage in Various Applications p. 26
• 3.3.2 Metadata: A Tool for Describing and Modeling Information p. 27
• 3.4 Ontologies: Vocabularies and Reference Terms for Metadata p. 30
• 3.5 Summary p. 33
• 4 Metadata Frameworks p. 35
• 4.1 Examples of Metadata Frameworks p. 35
• 4.1.1 XML-Based Metadata Framework p. 36
• 4.1.2 RDF-Based Metadata Framework p. 36
• 4.1.3 OWL-Based Metadata Framework p. 37
• 4.1.4 WSMO-Based Metadata Framework p. 37
• 4.2 Two Perspectives: Data Models and Model-Theoretic Semantics p. 38
• 4.2.1 Data Models p. 38
• 4.2.2 Multiple Syntaxes for RDF: A Short Note p. 47
• 4.2.3 Model-Theoretic Semantics p. 48
• 4.3 Query Languages p. 51
• 4.3.1 Query Languages for XML Data p. 51
• 4.3.2 Query Languages for RDF Data p. 62
• 4.3.3 Extending Query Languages with Reasoning and Entailment p. 73
• 4.4 Clinical Scenario Revisited p. 74
• 4.4.1 Semantic Web Specifications: LIMS and EMR Data p. 74
• 4.4.2 Linking data from Multiple Data Sources p. 76
• 4.4.3 Advantages and Disadvantages of using Semantic Web Specifications p. 78
• 4.5 Summary p. 78
• 5 Ontologies and Schemas p. 79
• 5.1 What is an Ontology? p. 79
• 5.2 Ontology Representation Languages p. 84
• 5.2.1 XML Schema p. 84
• 5.2.2 RDF Schema p. 92
• 5.2.3 Web Ontology Language p. 100
• 5.2.4 The Web Service Modeling Ontology (WSMO) p. 112
• 5.2.5 Comparison of Ontology Representation Languages p. 118
• 5.3 Integration of Ontology and Rule Languages p. 122
• 5.3.1 Motivation and Requirements p. 122
• 5.3.2 Overview of Languages and Approaches p. 123
• 5.3.3 Semantic Web Rules Language p. 124
• 5.4 Clinical Scenario Revisited p. 126
• 5.4.1 A Domain Ontology for Translational Medicine p. 126
• 5.4.2 Integration of Ontologies and Rules for Clinical Decision Support p. 130
• 5.4.3 Advantages and Disadvantages of using Semantic Web Specifications p. 135
• 5.5 Summary p. 135
• 6 Ontology Authoring and Management p. 137
• 6.1 Ontology Building Tools p. 137
• 6.1.1 Ontology Editors: Brief Descriptions p. 138
• 6.1.2 Ontology Editors: A Comparative Evaluation p. 143
• 6.2 Ontology Bootstrapping Approaches p. 148
• 6.3 Ontology Merge and Integration Tools p. 150
• 6.3.1 Ontology Merge and Integration Tools: A Brief Description p. 151
• 6.3.2 Evaluation of Ontology Merge and Integration Tools p. 152
• 6.4 Ontology Engines and Reasoners p. 154
• 6.5 Clinical Scenario Revisited p. 157
• 6.6 Summary p. 158
• 7 Applications of Metadata and Ontologies p. 161
• 7.1 Tools and Techniques for Metadata Annotation p. 161
• 7.1.1 Requirements for Metadata Annotation p. 162
• 7.1.2 Tools and Technologies for Metadata Annotation p. 163
• 7.1.3 Comparative Evaluation p. 168
• 7.2 Techniques for Schema/Ontology Mapping p. 173
• 7.2.1 A Classification of Schema-matching Approaches p. 173
• 7.2.2 Schema-matching Techniques: Overview p. 179
• 7.3 Ontology Driven Information Integration p. 183
• 7.3.1 The Role of Ontologies in Information Integration p. 183
• 7.3.2 Ontology Representations Used in Information Integration p. 187
• 7.3.3 The Role of Mapping in Information Integration p. 188
• 7.3.4 The Role of Ontology Engineering in Information Integration p. 190
• 7.4 Summary p. 192
• Part III Process Aspects of the Semantic Web p. 193
• 8 Communication p. 195
• 8.1 Communication Concepts p. 195
• 8.1.1 Fundamental Types p. 196
• 8.1.2 Formats and Protocols (FAP) p. 197
• 8.1.3 Separation of Interface and Logic p. 198
• 8.1.4 Communicating Parties p. 199
• 8.1.5 Mediation p. 201
• 8.1.6 Non-functional Aspects p. 202
• 8.2 Communication Paradigms p. 203
• 8.2.1 Client/Server (C/S) p. 204
• 8.2.2 Queueing p. 204
• 8.2.3 Peer-to-Peer (P2P) p. 205
• 8.2.4 Blackboard p. 205
• 8.2.5 Web Services p. 206
• 8.2.6 Representational State Transfer (REST) p. 207
• 8.2.7 Agents p. 207
• 8.2.8 Tuple Spaces p. 208
• 8.2.9 Co-location p. 208
• 8.2.10 Summary p. 209
• 8.3 Long-Running Communication p. 209
• 8.3.1 Business-to-Business (B2B) Protocols p. 210
• 8.3.2 Application-to-Application (A2A) Protocols p. 211
• 8.4 Web Services p. 211
• 8.5 Clinical Use Case p. 212
• 8.6 Summary p. 214
• 9 State of the Art in Web Services p. 215
• 9.1 History p. 215
• 9.2 Traditional Web Services p. 216
• 9.2.1 WSDL p. 217
• 9.2.2 SOAP p. 218
• 9.2.3 UDDI p. 219
• 9.2.4 Summary p. 219
• 9.3 Emerging Web Service Specifications (WS*-Stack) p. 220
• 9.3.1 Standards p. 220
• 9.3.2 Web Service Standards p. 221
• 9.3.3 Semantic-Web-Service-Related Standards p. 222
• 9.4 Service-oriented Architecture (SOA) p. 223
• 9.4.1 Service Paradigm p. 223
• 9.4.2 SOA and Web Services p. 224
• 9.4.3 Open Issues and Technical Challenges p. 224
• 9.5 Semantics and Web Services p. 226
• 9.5.1 Semantics, What Semantics? p. 227
• 9.5.2 Data Semantics p. 228
• 9.5.3 Process Semantics p. 229
• 9.5.4 Selection Semantics p. 229
• 9.5.5 Other Types of Semantics p. 230
• 9.6 Clinical Use Case p. 231
• 9.7 Summary p. 232
• 10 Web Service Composition p. 233
• 10.1 Composition p. 233
• 10.1.1 Motivation p. 233
• 10.1.2 Definition of Composition p. 235
• 10.1.3 Web Services and Composition p. 237
• 10.1.4 Choreography and Orchestration p. 238
• 10.2 Dynamic Composition p. 239
• 10.3 Business-to-Business Communication p. 240
• 10.4 Application-to-Application Communication p. 241
• 10.5 Complex Business Logic p. 242
• 10.6 Standards and Technologies p. 243
• 10.6.1 Web Services Business Process Execution Language (WS-BPEL) p. 244
• 10.6.2 Business Process Modeling Notation (BPMN) p. 245
• 10.6.3 Web Service Choreography Description Language (WS-CDL) p. 245
• 10.6.4 Java Business Integration (JBI) p. 246
• 10.7 Clinical Use Case p. 247
• 10.8 Summary p. 247
• 11 Semantic Web Services p. 249
• 11.1 Semantics of Web Services p. 249
• 11.1.1 Why Semantic Web Services? p. 249
• 11.1.2 Interface vs. Implementation p. 251
• 11.1.3 Modeling of State p. 251
• 11.2 Alternatives for Capturing Semantics of Web Services p. 253
• 11.2.1 Finite State Machines p. 253
• 11.2.2 Statechart Diagrams p. 254
• 11.2.3 Petri Nets p. 254
• 11.2.4 Process Algebras p. 256
• 11.3 Semantic Web Service Approaches p. 259
• 11.3.1 OWL-S p. 259
• 11.3.2 SWSF p. 261
• 11.3.3 WSDL-S p. 266
• 11.3.4 SAWSDL p. 268
• 11.3.5 WSMO, WSML and WSMX p. 269
• 11.4 Reasoning with Web Service Semantics p. 276
• 11.4.1 Discovery p. 276
• 11.4.2 Semantic Web Service Composition p. 281
• 11.4.3 Mediation p. 283
• 11.5 Clinical Use Case p. 285
• 11.6 Summary p. 286
• Part IV Standards p. 287
• 12 Semantic Web Standards p. 289
• 12.1 Relevant Standards Organization p. 289
• 12.1.1 International Organization for Standardization (ISO) p. 289
• 12.1.2 International Electotechnical Commission (IEC) p. 290
• 12.1.3 Organization for the Advancement of Structured Information Standards (OASIS) p. 290
• 12.1.4 World Wide Web Consortium (W3C) p. 290
• 12.1.5 International Engineering Task Force (IETF) p. 291
• 12.1.6 National Institute of Standards and Technology (NIST) p. 291
• 12.1.7 The Object Modeling Group (OMG) p. 291
• 12.1.8 Semantic Web Services Initiative (SWSI) p. 292
• 12.1.9 United States National Library of Medicine (NLM) p. 292
• 12.2 Semantic Web Content Standardization Efforts p. 293
• 12.2.1 Standard Generalized Markup Language (SGML) p. 293
• 12.2.2 eXtensible Markup Language (XML) p. 293
• 12.2.3 eXtensible Stylesheet Transformation Language (XSLT) p. 294
• 12.2.4 XPath p. 294
• 12.2.5 XQuery p. 294
• 12.2.6 XML Schema p. 294
• 12.2.7 Resource Description Framework (RDF) p. 295
• 12.2.8 SPARQL p. 295
• 12.2.9 RDF Schema p. 295
• 12.2.10 Web Ontology Language (OWL) p. 296
• 12.2.11 Rule-ML p. 296
• 12.2.12 Semantic Web Rules Language (SWRL) p. 296
• 12.2.13 Ontology Definition Metamodel (ODM) p. 296
• 12.2.14 Unified Modeling Language (UML) p. 297
• 12.2.15 Knowledge Interchange Format (KIF) p. 297
• 12.2.16 Open Knowledge Base Connectivity Protocol (OKBC) p. 297
• 12.2.17 DIG Description Logics Interface p. 297
• 12.2.18 OWL API p. 298
• 12.2.19 Standardized Vocabularies and Ontologies p. 298
• 12.3 Semantic Web Services Standardization Efforts p. 300
• 12.3.1 ISO-18629 Process Specification Language (PSL) p. 301
• 12.3.2 W3C Semantic Annotations for the Web Services Description Language (SAWSDL) p. 302
• 12.3.3 OWL-S p. 303
• 12.3.4 Web Services Modeling Ontology (WSMO) p. 303
• 12.3.5 Semantic Web Services Framework (SWSF) p. 304
• 12.3.6 WSDL-S p. 304
• 12.3.7 OASIS Semantic Execution Environment (SEE) p. 304
• 12.3.8 OASIS Service-Oriented Architecture Reference Model (SOA RM) p. 305
• 12.3.9 Semantic Web Services Architecture (SWSA) p. 306
• 12.3.10 Semantic Web Services Interest Group (SWS-IG) p. 307
• 12.4 Summary p. 307
• Part V Putting it All Together and Perspective p. 309
• 13 A Solution Approach to the Clinical Use Case p. 311
• 13.1 Service Discovery, Composition and Choreography p. 312
• 13.1.1 Specification of Clinical Workflow using WSMO p. 313
• 13.1.2 Data Structures in Data Flow p. 316
• 13.1.3 Data Mediation p. 319
• 13.1.4 Goal Definition p. 328
• 13.1.5 Discovery p. 331
• 13.1.6 Orchestration/Service Composition p. 333
• 13.1.7 Process and Protocol Mediation p. 339
• 13.2 Data and Knowledge Integration p. 342
• 13.2.1 Data Integration Services: WSMO/WSML Specification p. 343
• 13.2.2 Semantic Data Integration Architecture p. 344
• 13.2.3 A Domain Ontology for Translational Medicine p. 346
• 13.2.4 Use of RDF to represent Genomic and Clinical Data p. 351
• 13.2.5 The Integration Process p. 353
• 13.3 Decision Support p. 356
• 13.3.1 Decision Support Services: WSMO/WSML Specification p. 357
• 13.3.2 Architecture p. 358
• 13.3.3 Business Object Model Design p. 359
• 13.3.4 Rule Base Design p. 360
• 13.3.5 Definitions vs. Actions: Ontology Design p. 360
• 13.4 Knowledge Maintenance and Provenance p. 365
• 14 Outlook: The Good, the Bad and the Ugly? p. 369
• 14.1 The Good - Progress and Impact p. 369
• 14.2 The Bad - Major Obstacles to Overcome p. 371
• 14.3 The Ugly - Possible Prohibitors p. 372
• Part VI References and Index p. 375
• References p. 377
• Index p. 405