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Cover image for The semantic web : semantics for data and services on the web
Title:
The semantic web : semantics for data and services on the web
Personal Author:
Series:
Data-centric systems and applications
Publication Information:
Berlin : Springer, 2008
Physical Description:
xv, 414 p. : ill. ; 25 cm.
ISBN:
9783540764519
Subject Term:

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30000010194211 TK5105.88815 K37 2008 Open Access Book Book
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Summary

Summary

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.


Author Notes

Vipul Kashyap, PhD is a Senior Medical Informatician in the Clinical Informatics Research & Development group at Partners HealthCare System. He plays the role of a systems and information architect in the content of a platform for Clinical Knowledge Management Platform and creating of clinical information models in the context of the Enterprise Clinical Services architecture at Partners Healthcare System. Vipul has received his PhD from the Department of Computer Science at Rutgers University in New Brunswick that investigated the use of metadata and ontologies for information and knowledge management. He was a co-project manager of a Knowledge Management effort at Telcordia Technologies (formerly known as Bellcore) focused on knowledge sharing and reuse across Telcordia''s Professional Services Units. He was a fellow at the National Library of Medicine, and has held positions at Micro-electronics and Computer Technology Corporation (MCC) and the National Institute of Standards and Technology (NIST). Vipul has published 2 books on the topic of Semantics in Information Brokering and Integration, 40-50 articles in prestigious conferences and journals. He serves on the editorial boards of 3 journals and sits on the technical advisory board of an early stage companies developing semantics-based products. He also represents Partners on the W3C Advisory Committee and the EHR Technical Committee of the HealthCare Information Technology Standards Panel (HITSP).

Christoph Bussler is Staff Software Engineer at BEA Systems, Inc., working in the core WebLogic application server product development organization. Before joining BEA, Chris was architect at Cisco Systems, Inc. in San Jose, CA, USA, responsible for the service-oriented architecture at Cisco Systems'' Quote-to-Cash business unit. Before taking this position he was Science Foundation Ireland Professor at the National University of Ireland, Galway in Ireland and Executive Director of the Digital Enterprise Research Institute (DERI). In addition to his role as Executive Director of DERI, Chris led the Semantic Web Services research group at DERI. Chris has a Ph.D. in computer science from the University of Erlangen, Germany and a Master in computer science from the Technical University of Munich, Germany. Chris published a book titled ''B2B Integration'', two books on workflow management, over 100 research papers in journals and academic conferences, gave tutorials on several topics including B2B integration, workflow management and service-oriented architectures and was keynote speaker at many conferences and workshops on topics like workflow management, B2B and EAI integration as well as Semantic Web.

Matthew Moran is a Senior Design Engineer with the SOA R&D group at Nortel Networks (Ireland) Ltd. working on their Multimedia Contact Center product. Prior to that, he was a Research Engineer with the Digital Enterprise Research Institute (DERI) at the National University of Ireland, Galway (NUIG)., where he was co-founder and architect of the WSMX open source Semantic Web Service execution environment. Previously, Matthew gained extensive industrial experience as a software engineer over ten years in Ireland, Germany and Australia. He worked with MediaOne in Dublin, Ireland and Rumble Group in Sydney Australia as a Web design engineer focusing on the early integration of Web service technology into Web applications. Matthew is completing his PhD in Semantic Web Services with NUIG and has a Bachelor of Electronic Engineering Degree from the same university. He is co-author of thirteen research papers in academic journals and conferences as well as three book chapters on topics relating to Semantic Web Services. He is co-architect of the WSMX open source Semantic Web Service execution environment and is co-author of the OASIS Semantic Execution Environment working group. In addition, he has co-authored and presented tutorials at eightinternational conferences.


Table of Contents

Part I Preliminariesp. 1
1 Introductionp. 3
1.1 Motivation: Why Semantic Web?p. 4
1.2 A Framework for Semantic Webp. 5
1.3 Use Case: Translational Medicine Clinical Vignettep. 7
1.4 Scope and Organizationp. 9
2 Use Case and Functional Requirementsp. 11
2.1 Detailed Clinical Use Casep. 12
2.2 Stakeholders and Information Needsp. 13
2.3 Conceptual Architecturep. 15
2.4 Functional Requirementsp. 17
2.5 Research Issuesp. 18
2.6 Summaryp. 19
Part II Information Aspects of the Semantic Webp. 21
3 Semantic Web Contentp. 23
3.1 Nature of Web Contentp. 23
3.2 Nature of Semantic Web Contentp. 24
3.3 Metadatap. 25
3.3.1 Metadata Usage in Various Applicationsp. 26
3.3.2 Metadata: A Tool for Describing and Modeling Informationp. 27
3.4 Ontologies: Vocabularies and Reference Terms for Metadatap. 30
3.5 Summaryp. 33
4 Metadata Frameworksp. 35
4.1 Examples of Metadata Frameworksp. 35
4.1.1 XML-Based Metadata Frameworkp. 36
4.1.2 RDF-Based Metadata Frameworkp. 36
4.1.3 OWL-Based Metadata Frameworkp. 37
4.1.4 WSMO-Based Metadata Frameworkp. 37
4.2 Two Perspectives: Data Models and Model-Theoretic Semanticsp. 38
4.2.1 Data Modelsp. 38
4.2.2 Multiple Syntaxes for RDF: A Short Notep. 47
4.2.3 Model-Theoretic Semanticsp. 48
4.3 Query Languagesp. 51
4.3.1 Query Languages for XML Datap. 51
4.3.2 Query Languages for RDF Datap. 62
4.3.3 Extending Query Languages with Reasoning and Entailmentp. 73
4.4 Clinical Scenario Revisitedp. 74
4.4.1 Semantic Web Specifications: LIMS and EMR Datap. 74
4.4.2 Linking data from Multiple Data Sourcesp. 76
4.4.3 Advantages and Disadvantages of using Semantic Web Specificationsp. 78
4.5 Summaryp. 78
5 Ontologies and Schemasp. 79
5.1 What is an Ontology?p. 79
5.2 Ontology Representation Languagesp. 84
5.2.1 XML Schemap. 84
5.2.2 RDF Schemap. 92
5.2.3 Web Ontology Languagep. 100
5.2.4 The Web Service Modeling Ontology (WSMO)p. 112
5.2.5 Comparison of Ontology Representation Languagesp. 118
5.3 Integration of Ontology and Rule Languagesp. 122
5.3.1 Motivation and Requirementsp. 122
5.3.2 Overview of Languages and Approachesp. 123
5.3.3 Semantic Web Rules Languagep. 124
5.4 Clinical Scenario Revisitedp. 126
5.4.1 A Domain Ontology for Translational Medicinep. 126
5.4.2 Integration of Ontologies and Rules for Clinical Decision Supportp. 130
5.4.3 Advantages and Disadvantages of using Semantic Web Specificationsp. 135
5.5 Summaryp. 135
6 Ontology Authoring and Managementp. 137
6.1 Ontology Building Toolsp. 137
6.1.1 Ontology Editors: Brief Descriptionsp. 138
6.1.2 Ontology Editors: A Comparative Evaluationp. 143
6.2 Ontology Bootstrapping Approachesp. 148
6.3 Ontology Merge and Integration Toolsp. 150
6.3.1 Ontology Merge and Integration Tools: A Brief Descriptionp. 151
6.3.2 Evaluation of Ontology Merge and Integration Toolsp. 152
6.4 Ontology Engines and Reasonersp. 154
6.5 Clinical Scenario Revisitedp. 157
6.6 Summaryp. 158
7 Applications of Metadata and Ontologiesp. 161
7.1 Tools and Techniques for Metadata Annotationp. 161
7.1.1 Requirements for Metadata Annotationp. 162
7.1.2 Tools and Technologies for Metadata Annotationp. 163
7.1.3 Comparative Evaluationp. 168
7.2 Techniques for Schema/Ontology Mappingp. 173
7.2.1 A Classification of Schema-matching Approachesp. 173
7.2.2 Schema-matching Techniques: Overviewp. 179
7.3 Ontology Driven Information Integrationp. 183
7.3.1 The Role of Ontologies in Information Integrationp. 183
7.3.2 Ontology Representations Used in Information Integrationp. 187
7.3.3 The Role of Mapping in Information Integrationp. 188
7.3.4 The Role of Ontology Engineering in Information Integrationp. 190
7.4 Summaryp. 192
Part III Process Aspects of the Semantic Webp. 193
8 Communicationp. 195
8.1 Communication Conceptsp. 195
8.1.1 Fundamental Typesp. 196
8.1.2 Formats and Protocols (FAP)p. 197
8.1.3 Separation of Interface and Logicp. 198
8.1.4 Communicating Partiesp. 199
8.1.5 Mediationp. 201
8.1.6 Non-functional Aspectsp. 202
8.2 Communication Paradigmsp. 203
8.2.1 Client/Server (C/S)p. 204
8.2.2 Queueingp. 204
8.2.3 Peer-to-Peer (P2P)p. 205
8.2.4 Blackboardp. 205
8.2.5 Web Servicesp. 206
8.2.6 Representational State Transfer (REST)p. 207
8.2.7 Agentsp. 207
8.2.8 Tuple Spacesp. 208
8.2.9 Co-locationp. 208
8.2.10 Summaryp. 209
8.3 Long-Running Communicationp. 209
8.3.1 Business-to-Business (B2B) Protocolsp. 210
8.3.2 Application-to-Application (A2A) Protocolsp. 211
8.4 Web Servicesp. 211
8.5 Clinical Use Casep. 212
8.6 Summaryp. 214
9 State of the Art in Web Servicesp. 215
9.1 Historyp. 215
9.2 Traditional Web Servicesp. 216
9.2.1 WSDLp. 217
9.2.2 SOAPp. 218
9.2.3 UDDIp. 219
9.2.4 Summaryp. 219
9.3 Emerging Web Service Specifications (WS*-Stack)p. 220
9.3.1 Standardsp. 220
9.3.2 Web Service Standardsp. 221
9.3.3 Semantic-Web-Service-Related Standardsp. 222
9.4 Service-oriented Architecture (SOA)p. 223
9.4.1 Service Paradigmp. 223
9.4.2 SOA and Web Servicesp. 224
9.4.3 Open Issues and Technical Challengesp. 224
9.5 Semantics and Web Servicesp. 226
9.5.1 Semantics, What Semantics?p. 227
9.5.2 Data Semanticsp. 228
9.5.3 Process Semanticsp. 229
9.5.4 Selection Semanticsp. 229
9.5.5 Other Types of Semanticsp. 230
9.6 Clinical Use Casep. 231
9.7 Summaryp. 232
10 Web Service Compositionp. 233
10.1 Compositionp. 233
10.1.1 Motivationp. 233
10.1.2 Definition of Compositionp. 235
10.1.3 Web Services and Compositionp. 237
10.1.4 Choreography and Orchestrationp. 238
10.2 Dynamic Compositionp. 239
10.3 Business-to-Business Communicationp. 240
10.4 Application-to-Application Communicationp. 241
10.5 Complex Business Logicp. 242
10.6 Standards and Technologiesp. 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 Casep. 247
10.8 Summaryp. 247
11 Semantic Web Servicesp. 249
11.1 Semantics of Web Servicesp. 249
11.1.1 Why Semantic Web Services?p. 249
11.1.2 Interface vs. Implementationp. 251
11.1.3 Modeling of Statep. 251
11.2 Alternatives for Capturing Semantics of Web Servicesp. 253
11.2.1 Finite State Machinesp. 253
11.2.2 Statechart Diagramsp. 254
11.2.3 Petri Netsp. 254
11.2.4 Process Algebrasp. 256
11.3 Semantic Web Service Approachesp. 259
11.3.1 OWL-Sp. 259
11.3.2 SWSFp. 261
11.3.3 WSDL-Sp. 266
11.3.4 SAWSDLp. 268
11.3.5 WSMO, WSML and WSMXp. 269
11.4 Reasoning with Web Service Semanticsp. 276
11.4.1 Discoveryp. 276
11.4.2 Semantic Web Service Compositionp. 281
11.4.3 Mediationp. 283
11.5 Clinical Use Casep. 285
11.6 Summaryp. 286
Part IV Standardsp. 287
12 Semantic Web Standardsp. 289
12.1 Relevant Standards Organizationp. 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 Effortsp. 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 XPathp. 294
12.2.5 XQueryp. 294
12.2.6 XML Schemap. 294
12.2.7 Resource Description Framework (RDF)p. 295
12.2.8 SPARQLp. 295
12.2.9 RDF Schemap. 295
12.2.10 Web Ontology Language (OWL)p. 296
12.2.11 Rule-MLp. 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 Interfacep. 297
12.2.18 OWL APIp. 298
12.2.19 Standardized Vocabularies and Ontologiesp. 298
12.3 Semantic Web Services Standardization Effortsp. 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-Sp. 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-Sp. 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 Summaryp. 307
Part V Putting it All Together and Perspectivep. 309
13 A Solution Approach to the Clinical Use Casep. 311
13.1 Service Discovery, Composition and Choreographyp. 312
13.1.1 Specification of Clinical Workflow using WSMOp. 313
13.1.2 Data Structures in Data Flowp. 316
13.1.3 Data Mediationp. 319
13.1.4 Goal Definitionp. 328
13.1.5 Discoveryp. 331
13.1.6 Orchestration/Service Compositionp. 333
13.1.7 Process and Protocol Mediationp. 339
13.2 Data and Knowledge Integrationp. 342
13.2.1 Data Integration Services: WSMO/WSML Specificationp. 343
13.2.2 Semantic Data Integration Architecturep. 344
13.2.3 A Domain Ontology for Translational Medicinep. 346
13.2.4 Use of RDF to represent Genomic and Clinical Datap. 351
13.2.5 The Integration Processp. 353
13.3 Decision Supportp. 356
13.3.1 Decision Support Services: WSMO/WSML Specificationp. 357
13.3.2 Architecturep. 358
13.3.3 Business Object Model Designp. 359
13.3.4 Rule Base Designp. 360
13.3.5 Definitions vs. Actions: Ontology Designp. 360
13.4 Knowledge Maintenance and Provenancep. 365
14 Outlook: The Good, the Bad and the Ugly?p. 369
14.1 The Good - Progress and Impactp. 369
14.2 The Bad - Major Obstacles to Overcomep. 371
14.3 The Ugly - Possible Prohibitorsp. 372
Part VI References and Indexp. 375
Referencesp. 377
Indexp. 405
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