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| Contents | ||||||
| Part I | Preliminaries | 1 | ||||
| 1 | Introduction | 3 | ||||
| 1.1 | Motivation: Why Semantic Web? | 4 | ||||
| 1.2 | A Framework for Semantic Web | 5 | ||||
| 1.3 | Use Case : Translational Medicine Clinical Vignette | 7 | ||||
| 1.4 | Scope and Organization | 9 | ||||
| 2 | Use Case and Functional Requirements | 11 | ||||
| 2.1 | Detailed Clinical Use Case | 12 | ||||
| 2.2 | Stakeholders and Information Needs | 13 | ||||
| 2.3 | Conceptual Architecture | 15 | ||||
| 2.4 | Functional Requirements | 17 | ||||
| 2.5 | Research Issues | 18 | ||||
| 2.6 | Summary | 19 | ||||
| Part II | Information Aspects of the Semantic Web | 21 | ||||
| 3 | Semantic Web Content | 23 | ||||
| 3.1 | Nature of Web Content | 23 | ||||
| 3.2 | Nature of Semantic Web Content | 24 | ||||
| 3.3 | Metadata | 25 | ||||
| 3.3.1 | Metadata Usage in Various Applications | 26 | ||||
| 3.3.2 | Metadata: A Tool for Describing and Modeling Information | 27 | ||||
| 3.4 | Ontologies : Vocabularies and Reference Terms for Metadata | 30 | ||||
| 3.5 | Summary | 33 | ||||
| 4 | Metadata Frameworks | 35 | ||||
| 4.1 | Examples of Metadata Frameworks | 35 | ||||
| 4.1.1 | XML-Based Metadata Framework | 36 | ||||
| 4.1.2 | RDF-Based Metadata Framework | 36 | ||||
| 4.1.3 | OWL-Based Metadata Framework | 37 | ||||
| 4.1.4 | WSMO-Based Metadata Framework | 37 | ||||
| 4.2 | Two Perspectives: Data Models and Model-Theoretic Semantics | 38 | ||||
| 4.2.1 | Data Models | 38 | ||||
| 4.2.2 | Multiple Syntaxes for RDF: A Short Note | 47 | ||||
| 4.2.3 | Model-Theoretic Semantics | 48 | ||||
| 4.3 | Query Languages | 51 | ||||
| 4.3.1 | Query Languages for XML Data | 51 | ||||
| 4.3.2 | Query Languages for RDF Data | 62 | ||||
| 4.3.3 | Extending Query Languages with Reasoning and Entailment | 73 | ||||
| 4.4 | Clinical Scenario Revisited | 74 | ||||
| 4.4.1 | Semantic Web Specifications: LIMS and EMR Data | 74 | ||||
| 4.4.2 | Linking data from Multiple Data Sources | 76 | ||||
| 4.4.3 | Advantages and Disadvantages of using Semantic Web Specifications | 78 | ||||
| 4.5 | Summary | 78 | ||||
| 5 | Ontologies and Schemas | 79 | ||||
| 5.1 | What is an Ontology? | 79 | ||||
| 5.2 | Ontology Representation Languages | 84 | ||||
| 5.2.1 | XML Schema | 84 | ||||
| 5.2.2 | RDF Schema | 92 | ||||
| 5.2.3 | Web Ontology Language | 100 | ||||
| 5.2.4 | The Web Service Modeling Ontology (WSMO) | 112 | ||||
| 5.2.5 | Comparison of Ontology Representation Languages | 118 | ||||
| 5.3 | Integration of Ontology and Rule Languages | 122 | ||||
| 5.3.1 | Motivation and Requirements | 122 | ||||
| 5.3.2 | Overview of Languages and Approaches | 123 | ||||
| 5.3.3 | Semantic Web Rules Language | 124 | ||||
| 5.4 | Clinical Scenario Revisited | 126 | ||||
| 5.4.1 | A Domain Ontology for Translational Medicine | 126 | ||||
| 5.4.2 | Integration of Ontologies and Rules for Clinical Decision Support | 130 | ||||
| 5.4.3 | Advanatages and Disadvantages of using Semantic Web Specifications | 135 | ||||
| 5.5 | Summary | 135 | ||||
| 6 | Ontology Authoring and Management | 137 | ||||
| 6.1 | Ontology Building Tools | 137 | ||||
| 6.1.1 | Ontology Editors: Brief Descriptions | 138 | ||||
| 6.1.2 | Ontology Editors : A Comparative Evaluation | 143 | ||||
| 6.2 | Ontology Bootstrapping Approaches | 148 | ||||
| 6.3 | Ontology Merge and Integration Tools | 150 | ||||
| 6.3.1 | Ontology Merge and Integration Tools : A Brief Description | 151 | ||||
| 6.3.2 | Evaluation of Ontology Merge and Integration Tools | 152 | ||||
| 6.4 | Ontology Engines and Reasoners | 154 | ||||
| 6.5 | Clinical Scenario Revisited | 157 | ||||
| 6.6 | Summary | 158 | ||||
| 7 | Applications of Metadata and Ontologies | 161 | ||||
| 7.1 | Tools and Techniques for Metadata Annotation | 161 | ||||
| 7.1.1 | Requirements for Metadata Annotation | 162 | ||||
| 7.1.2 | Tools and Technologies for Metadata Annotation | 163 | ||||
| 7.1.3 | Comparative Evaluation | 168 | ||||
| 7.2 | Techniques for Schema/Ontology Mapping | 173 | ||||
| 7.2.1 | A Classification of Schema-matching Approaches | 173 | ||||
| 7.2.2 | Schema-matching Techniques: Overview | 179 | ||||
| 7.3 | Ontology Driven Information Integration | 183 | ||||
| 7.3.1 | The Role of Ontologies in Information Integration | 183 | ||||
| 7.3.2 | Ontology Representations Used in Information Integration | 187 | ||||
| 7.3.3 | The Role of Mapping in Information Integration | 188 | ||||
| 7.3.4 | The Role of Ontology Engineering in Information Integration | 190 | ||||
| 7.4 | Summary | 192 | ||||
| Part III | Process Aspects of the Semantic Web | 193 | ||||
| 8 | Communication | 195 | ||||
| 8.1 | Communication Concepts | 195 | ||||
| 8.1.1 | Fundamental Types | 196 | ||||
| 8.1.2 | Formats and Protocols (FAP) | 197 | ||||
| 8.1.3 | Separation of Interface and Logic | 198 | ||||
| 8.1.4 | Communicating Parties | 199 | ||||
| 8.1.5 | Mediation | 201 | ||||
| 8.1.6 | Non-functional Aspects | 202 | ||||
| 8.2 | Communication Paradigms | 203 | ||||
| 8.2.1 | Client/Server (C/S) | 204 | ||||
| 8.2.2 | Queueing | 204 | ||||
| 8.2.3 | Peer-to-Peer (P2P) | 205 | ||||
| 8.2.4 | Blackboard | 205 | ||||
| 8.2.5 | Web Services | 206 | ||||
| 8.2.6 | Representational State Transfer (REST) | 207 | ||||
| 8.2.7 | Agents | 207 | ||||
| 8.2.8 | Tuple Spaces | 208 | ||||
| 8.2.9 | Co-location | 208 | ||||
| 8.2.10 | Summary | 209 | ||||
| 8.3 | Long-Running Communication | 209 | ||||
| 8.3.1 | Business-to-Business (B2B) Protocols | 210 | ||||
| 8.3.2 | Application-to-Application (A2A) Protocols | 211 | ||||
| 8.4 | Web Services | 211 | ||||
| 8.5 | Clinical Use Case | 212 | ||||
| 8.6 | Summary | 214 | ||||
| 9 | State of the Art in Web Services | 215 | ||||
| 9.1 | History | 215 | ||||
| 9.2 | Traditional Web Services | 216 | ||||
| 9.2.1 | WSDL | 217 | ||||
| 9.2.2 | SOAP | 218 | ||||
| 9.2.3 | UDDI | 219 | ||||
| 9.2.4 | Summary | 219 | ||||
| 9.3 | Emerging Web Service Specifications (WS*-Stack) | 220 | ||||
| 9.3.1 | Standards | 220 | ||||
| 9.3.2 | Web Service Standards | 221 | ||||
| 9.3.3 | Semantic-Web-Service-Related Standards | 222 | ||||
| 9.4 | Service-oriented Architecture (SOA) | 223 | ||||
| 9.4.1 | Service Paradigm | 223 | ||||
| 9.4.2 | SOA and Web Services | 224 | ||||
| 9.4.3 | Open Issues and Technical Challenges | 224 | ||||
| 9.5 | Semantics and Web Services | 226 | ||||
| 9.5.1 | Semantics, What Semantics? | 227 | ||||
| 9.5.2 | Data Semantics | 228 | ||||
| 9.5.3 | Process Semantics | 229 | ||||
| 9.5.4 | Selection Semantics | 229 | ||||
| 9.5.5 | Other Types of Semantics | 230 | ||||
| 9.6 | Clinical Use Case | 231 | ||||
| 9.7 | Summary | 232 | ||||
| 10 | Web Service Composition | 233 | ||||
| 10.1 | Composition | 233 | ||||
| 10.1.1 | Motivation | 233 | ||||
| 10.1.2 | Definition of Composition | 235 | ||||
| 10.1.3 | Web Services and Composition | 237 | ||||
| 10.1.4 | Choreography and Orchestration | 238 | ||||
| 10.2 | Dynamic Composition | 239 | ||||
| 10.3 | Business-to-Business Communication | 240 | ||||
| 10.4 | Application-to-Application Communication | 241 | ||||
| 10.5 | Complex Business Logic | 242 | ||||
| 10.6 | Standards and Technologies | 243 | ||||
| 10.6.1 | Web Services Business Process Execution Language (WS-BPEL) | 244 | ||||
| 10.6.2 | Business Process Modeling Notation (BPMN) | 245 | ||||
| 10.6.3 | Web Service Choreography Description Language (WS-CDL) | 245 | ||||
| 10.6.4 | Java Business Integration (JBI) | 246 | ||||
| 10.7 | Clinical Use Case | 247 | ||||
| 10.8 | Summary | 247 | ||||
| 11 | Semantic Web Services | 249 | ||||
| 11.1 | Semantics of Web Services | 249 | ||||
| 11.1.1 | Why Semantic Web Services? | 249 | ||||
| 11.1.2 | Interface vs. Implementation | 251 | ||||
| 11.1.3 | Modeling of State | 251 | ||||
| 11.2 | Alternatives for Capturing Semantics of Web Services | 253 | ||||
| 11.2.1 | Finite State Machines | 253 | ||||
| 11.2.2 | Statechart Diagrams | 254 | ||||
| 11.2.3 | Petri Nets | 254 | ||||
| 11.2.4 | Process Algebras | 256 | ||||
| 11.3 | Semantic Web Service Approaches | 259 | ||||
| 11.3.1 | OWL-S | 259 | ||||
| 11.3.2 | SWSF | 261 | ||||
| 11.3.3 | WSDL-S | 266 | ||||
| 11.3.4 | SAWSDL | 268 | ||||
| 11.3.5 | WSMO, WSML and WSMX | 269 | ||||
| 11.4 | Reasoning with Web Service Semantics | 276 | ||||
| 11.4.1 | Discovery | 276 | ||||
| 11.4.2 | Semantic Web Service Composition | 281 | ||||
| 11.4.3 | Mediation | 283 | ||||
| 11.5 | Clinical Use Case | 285 | ||||
| 11.6 | Summary | 286 | ||||
| Part IV | Standards | 287 | ||||
| 12 | Semantic Web Standards | 289 | ||||
| 12.1 | Relevant Standards Organization | 289 | ||||
| 12.1.1 | International Organization for Standardization (ISO) | 289 | ||||
| 12.1.2 | International Electotechnical Commission (IEC) | 290 | ||||
| 12.1.3 | Organization for the Advancement of Structured Information Standards (OASIS) | 290 | ||||
| 12.1.4 | World Wide Web Consortium (W3C) | 290 | ||||
| 12.1.5 | International Engineering Task Force (IETF) | 291 | ||||
| 12.1.6 | National Institute of Standards and Technology (NIST) | 291 | ||||
| 12.1.7 | The Object Modeling Group (OMG) | 291 | ||||
| 12.1.8 | Semantic Web Services Initiative (SWSI) | 292 | ||||
| 12.1.9 | United States National Library of Medicine (NLM) | 292 | ||||
| 12.2 | Semantic Web Content Standardization Efforts | 293 | ||||
| 12.2.1 | Standard Generalized Markup Language (SGML) | 293 | ||||
| 12.2.2 | extensible Markup Language (XML) | 293 | ||||
| 12.2.3 | extensible Stylesheet Transformation Language (XSLT) | 294 | ||||
| 12.2.4 | XPath | 294 | ||||
| 12.2.5 | XQuery | 294 | ||||
| 12.2.6 | XML Schema | 294 | ||||
| 12.2.7 | Resource Description Framework (RDF) | 295 | ||||
| 12.2.8 | SPARQL | 295 | ||||
| 12.2.9 | RDF Schema | 295 | ||||
| 12.2.10 | Web Ontology Language (OWL) | 296 | ||||
| 12.2.11 | Rule-ML | 296 | ||||
| 12.2.12 | Semantic Web Rules Language (SWRL) | 296 | ||||
| 12.2.13 | Ontology Definition Metamodel (ODM) | 296 | ||||
| 12.2.14 | Unified Modeling Language (UML) | 297 | ||||
| 12.2.15 | Knowledge Interchange Format (KIF) | 297 | ||||
| 12.2.16 | Open Knowledge Base Connectivity Protocol (OKBC) | 297 | ||||
| 12.2.17 | DIG Description Logics Interface | 297 | ||||
| 12.2.18 | OWL API | 298 | ||||
| 12.2.19 | Standardized Vocabularies and Ontologies | 298 | ||||
| 12.3 | Semantic Web Services Standardization Efforts | 300 | ||||
| 12.3.1 | ISO-18629 Process Specification Language (PSL) | 301 | ||||
| 12.3.2 | W3C Semantic Annotations for the Web Services Description Language (SAWSDL) | 302 | ||||
| 12.3.3 | OWL-S | 303 | ||||
| 12.3.4 | Web Services Modeling Ontology (WSMO) | 303 | ||||
| 12.3.5 | Semantic Web Services Framework (SWSF) | 304 | ||||
| 12.3.6 | WSDL-S | 304 | ||||
| 12.3.7 | OASIS Semantic Execution Environment (SEE) | 304 | ||||
| 12.3.8 | OASIS Service-Oriented Architecture Reference Model (SOA RM) | 305 | ||||
| 12.3.9 | Semantic Web Services Architecture (SWSA) | 306 | ||||
| 12.3.10 | Semantic Web Services Interest Group (SWS-IG) | 307 | ||||
| 12.4 | Summary | 307 | ||||
| Part V | Putting it All Together and Perspective | 309 | ||||
| 13 | A Solution Approach to the Clinical Use Case | 311 | ||||
| 13.1 | Service Discovery, Composition and Choreography | 312 | ||||
| 13.1.1 | Specification of Clinical Workflow using WSMO | 313 | ||||
| 13.1.2 | Data Structures in Data Flow | 316 | ||||
| 13.1.3 | Data Mediation | 319 | ||||
| 13.1.4 | Goal Definition | 328 | ||||
| 13.1.5 | Discovery | 331 | ||||
| 13.1.6 | Orchestration/Service Composition | 333 | ||||
| 13.1.7 | Process and Protocol Mediation | 339 | ||||
| 13.2 | Data and Knowledge Integration | 342 | ||||
| 13.2.1 | Data Integration Services: WSMO/WSML Specification | 343 | ||||
| 13.2.2 | Semantic Data Integration Architecture | 344 | ||||
| 13.2.3 | A Domain Ontology for Translational Medicine | 346 | ||||
| 13.2.4 | Use of RDF to represent Genomic and Clinical Data | 351 | ||||
| 13.2.5 | The Integration Process | 353 | ||||
| 13.3 | Decision Support | 356 | ||||
| 13.3.1 | Decision Support Services: WSMO/WSML Specification | 357 | ||||
| 13.3.2 | Architecture | 358 | ||||
| 13.3.3 | Business Object Model Design | 359 | ||||
| 13.3.4 | Rule Base Design | 360 | ||||
| 13.3.5 | Definitions vs. Actions: Ontology Design | 360 | ||||
| 13.4 | Knowledge Maintenance and Provenance | 365 | ||||
| 14 | Outlook: The Good, the Bad and the Ugly? | 369 | ||||
| 14.1 | The Good - Progress and Impact | 369 | ||||
| 14.2 | The Bad - Major Obstacles to Overcome | 371 | ||||
| 14.3 | The Ugly - Possible Prohibitors | 372 | ||||
| Part VI | References and Index | 375 | ||||
| References | 377 | |||||
| Index | 405 | |||||
Preface
A decade ago Tim Berners-Lee proposed an extraordinary vision: despite the phenomenal 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 reasoning 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 wholesystem 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 communities are ideal incubators: knowledge-driven, fragmented, diverse, a range of structured 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 demanding requirements for trust, security, fidelity and expressivity.
This book is the first to describe comprehensively the two main characteristics of the Semantic Web - its information and its processes - and to apply it not to toy, artificial examples but to a challenging application that matters, namely translational medicine. As such, it will become a key text for all of those serious about discovering the many facets of the Semantic Web, those who need to understand the current state of the art as it really is in practice, and those who need to be knowledgeable about its future.
Professor Carole Goble
University of Manchester
DATA-CENTRIC SYSTEMS AND APPLICATIONS
Advanced data management is the backbone of all information processing and has been one of the core topics in computer science from the start. The emphasis in this series is on timely publication of books on topics relevant to the development of data-centric systems and applications.
Books in the series have strong practical or application relevance as well as a thorough scientific basis. They will be of particular interest to researchers and professionals wishing to learn about new relevant concepts and topics, as they emphasize both the underlying technologies and their use in developing practical solutions.
Editors-in-Chief Michael J. Carey and Stefano Ceri
Kashyap Bussler Moran
The Semantic Web
The Semantic Web is a vision - the idea of having data on the Web defined and linked in such a way that it can be used by machines not just for display purposes but for automation, integration and reuse of data across various applications. Technically, however, there is a widespread misconception that the Semantic Web is primarily a rehash of existing Al and database work focused on encoding knowledge representation formalisms in markup languages such as RDF(S), DAML+OIL or OWL.
Kashyap, Bussler, and Moran seek to dispel this notion by presenting the broad dimensions of this emerging Semantic Web and the multi-disciplinary technological underpinnings like machine learning, information retrieval, service-oriented architectures, and grid computing, thus combining the informational and computational aspects needed to realize the full potential of the Semantic Web vision. Throughout the book, the use-case of a clinical vignette will serve to motivate and explain solutions based on Semantic Web technologies, emphasizing the application aspects related to data integration, knowledge acquisition, change management, semantic web services, and workflow management.
With this textbook, the authors deliver an application-driven state-of-the-art presentation of Semantic Web technologies, ideally suited for academic courses on the Semantic Web and architectures of information systems, and for self-studying professionals engaged in the design and implementation of advanced application systems.
ISBN 978-3-540-76451-9
Index
Aabstract processes 244, 245
Abstract service discovery 280
Abstract State Machine (ASM) 272
activities 245
Adaptive IE 166
Adaptive Information Extraction 168
Aero-DAML 167, 168
Aero-SWARM8 167
AI Planning 281
Aktive-Doc 168
ALCQHIR 156
AL-log 187
Amaya 164
Amilcare 165, 166
analog telephone 196
Anchor-PROMPT 181
annotation frameworks, tools and environments 163
Annotation Process 191
annotation process 162
Annotation Storage 163
Annotea 163
Annozilla 164
Apollo 138
Application-to-Application (A2A) Protocols 211
Application-to-Application Communication 241
Armadillo 166, 168
Artemis 179
artifacts 245
assumptions 271
asynchronous communication 195
asynchronous connection 196
ATP 147
autonomous systems 234
BBasic Formal Ontology (BFO) 300
behavior of communication 198
best profile covering 277
BFO 84
BioPAX 18
BioPax 32, 299
BPEL 222
BPEL4WS 244
BPMN 222
Business Process Modeling Notation (BPMN) 245
Business-to-Business (B2B) Protocols 210
Business-to-Business Communication240
BUSTER 186, 187, 188
CC++ 139
CAFETIERE 166, 168
Capability 271
CARIN 123, 187
Carnot 183
CEL 154
Chimaera 151
Choreography 238
choreography 246, 272
Ciao Prolog 147
CIM/DMTF 298
Classes 96
CLASSIC 149, 187
Classification 80
Classification of Schema-matching Approaches 173
Clinical Use Case 12
clinical workflow 311
COBra 141
COBWEB 149
Coding Systems 80
COHSE 164
COIN 186, 187
collaboration 245
COMA 180
combination of business logic 243
Combination of matchers 173
combination of several specialized ontologies 185
Combination ofMAtching algorithms (COMA) 180
Common Information Model (CIM) 82
communication 195
communication channel 196
communication partners 195
communication protocols 195
community of agents 79
Comparison of Ontology Representation Languages 118
compensating actions 245
compensation 237
Complex types 87
component invocation 235
composed components 235
composed objects 235
composing object). 235
composition 233, 243
composition implementation 239
Composition in context of communication 234
Composition in context of complex business logic 234
Computational Aspects of the Semantic Web 7
conditional branching 235
conjunction 120
connecting objects 245
connection 196
containment principle 234
Content Models 90
Context 118
CORBA215
CREAM 163, 164
Cupid 179
Cyc 299
Cyc Ontology 32
DDAML 260
DAML+OIL 303
DAML-ONT 303
DAML-S 260, 303
DARPA Agent Markup Language (DAML) 303
data flow 236
data formats 195
Data mediation 274, 340
data mediation 284
Data Model 35
Data Models and Semantics 38
data sources 236
Datalog 187
declarative compositions 235
deep Web 23
Defined Mappings 189
Definition of Composition 235
Définition of Terms 188
Description Logics 116
description logics 100, 187
description logics (DL) 178
description logics (DL) EL 154
Description Logics Program (DLP) 124
Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) 177
DIG Description Logics Interface 297
DIP 303
Direct 3D 165
Discovery 276
disjunction 120
Distributed Management Task Force 82
distributed transactions 237
DLEL+155
DL reasoners 147
DLS 170
Document and Annotation consistency 163
document classification and composition 29
document vectors 29
DOLCE 84
domain ontology 186
Domain Specific Metadata 28
domain specific ontology 185
DWQ 183, 187, 188, 189, 191
Dynamic Composition 239
dynamic composition 233
EEDI 210
effects 271
Electronic Health Record (EHR) 15
Elementary matchers 173
Enterprise Application Integration (EAI) 211, 241
Entity-Relationship Models 81
exactly-once transmission 210
exceptions 245
executable processes 244
explicit composition 234
Expose 191
Expressive XML Query Languages 53
Extended Entity-Relationship (EER) 140
extensible Markup Language (XML)35, 293
Extensible Stylesheet language (XSL)36
extensible Stylesheet Transformation Language (XSLT) 294
external behavior 238
externally visible behavior 238
FFaCT++ 155
Finite State Machines 253
First-Order Logic 116
First-Order Logic Ontology for Web Services (FLOWS) 261, 302
F-Logic 187 flow objects 245
FLOWS-Core 263 formats and protocols 197foundation ontology 84
Frame Representation Systems (FRSs) 141
Framework for Semantic Web 5 fuzzy-DL 155
GGalen Medical Knowledge Base (GALEN) 155
GALEN methodology 146
GATE 167
Gene Ontology 18, 32, 298
Gene Ontology (GO) 155
general concept inclusions (GCI) 154
general ontology 186
Generic Knowledge Base (GKB) Editor 141
GENIA biomedical corpus 166
GGMediators 274
global ontology 184
global processes 245
GO 141
Goal 270
Goal discovery 280
Goal refinement 280
goal-based orchestration 283
GRAIL 187
Graphic Query Interfaces 53
HHaystack 168
Hierarchical Task Planning (HTN) 282
Higher Order Theories 83
HIPP A A 210
Horn Rules 124
horn rules 188
h-Tech-Sight Knowledge Management Platform 167
HTTP 218
hybrid ontology approach 184
IICD-10 17
I-COM 191
ICOM 140
IEEE Standard Upper Ontology (IEEE SUO) 32
IEEE Suggested Upper Merged Ontology (SUMO) 300
Implementation 251
implicit composition 234
Impression vectors 29
inference engines 147
Information Aspects of the Semantic Web 6
information types 245
Info-Sleuth 183, 187, 190
Inheritance 120
instance document 84
Instances 119
Integrated Annotation Environments 168
Inter-domain specific metadata 29
Interface 251
interface 272
internal behavior 238
internal processes 245
International Classification of Diseases 32
International Classification of Diseases (ICD) 80
International Classification of Diseases (ICD-9) 299
International Electotechnical Commission (IEC) 290
International Engineering Task Force (IETF) 291
International Organization for Standardization (ISO) 289
Inter-Ontology Mapping 189
inter-ontology mapping 185
Intra-domain specific metadata 28
inverted indices 29
invocation order 235
IODE 140
ISO-18629
Process Specification Language (PSL) 301
JJava Business Integration (JBI) 246
Java Management Extensions (JMX) 276
Java-Spaces 276
JPEG 2000 165
KK@ 166
KAON2 155
KEGG32
Keyword-Based Discovery 277
keyword-based discovery 277
KIF139
KIM 167
KIMO ontology 167
Know-ItAll 166
knowledge engineer 14
Knowledge Interchange Format (KIF) 32, 83, 261, 297, 301
KRAFT 183, 187, 188, 189, 190
KRSS 139
LLabel Bureaus 170
Laboratory Information Management Systems (LIMS) 15
Lexical Relations 189
LinKFactory 138
List Types 90
Lixto 166
logic DLR 187
Logic Programming 116
Long-running Communication 209
long-running transaction 243
long-running transactions 236
LOOM 191
Loom 139, 147
LOOM description logic 187
Lorel51, 54
MMagpie 168
Mangrove 164
Mealy machines 253
MECOTA 186
Mediation 283
Mediator 270
Medical Subject Headings (MeSH) 299
Medical Subjects Heading 32
MEDLINE 30
Melita 166, 172
Meta-Annotation 188
Metadata 25
Metadata Annotation Frameoworks 163
Metadata Annotation Tools 164
metadata annotations of structured web resources 161
Meta-Object Facility (MOF) 37
metdata annotations of unstructured and semi-structured docments 161
METEOR-S 266
METHONTOLOGY 139
Methontology 146
minimal ontology commitment 184
MnM 166
Model-Theoretic Semantics 48
Modularization 234
MOMIS mediator system 179
monolithic ontology 185
M-Onto-Mat-Annotizer 165
Moore machines 253
Mozilla 164
MPEG-2 165
multi-party communication 199
Multiple ontologies and evolution 162
Multiple Ontology Approach 185
multiple ontology approach 184
NN3 62
Naive Ontology Mapping (NOM) 180
National Institute of Standards and Technology (NIST) 291
Natural Language Processing (NLP) 148
NDVI29
Negation 120
New Types 91
Nomenclature 80
OOASIS SOA reference model (RM) 223
Object Management Group (OMG) 37
Object Query Language (OQL) 54
object-based discovery 277
OBO 141
OBSERVER 183, 185, 187, 188, 189
Occurrence Constraints 88
OCML 140
OCML inference engine 147
ODEMerge 151
OIL 187, 260
OKBC (Open Knowledge Based Connectivity) 139
Onto-Broker 147
Ontobroker 183, 187, 188, 190
Onto-edit 191
Onto-Knowledge methodology 146
Ontolingua 139, 147, 185
Ontolingua Server 139
Ontologies 30
Ontologies as Verification Mechanism 186
Ontology 270
ontology as a query model 186
Ontology Bootstrapping 148
Ontology Building Tools 137
Ontology Definition Metamodel (ODM) 296
Ontology Development Methodologies 190 *Ontology Editors 138
Ontology Engines and Reasoners 154
ontology evolution 191
Ontology Inference Language (OIL)303
Ontology Merge and Integration Tools150
Ontology Representation Languages84
ontology-based information integration 183
Onto-Mat-Annotizer 164, 165
Ontosaurus 139, 147
Onto-Studio 138, 147, 191
Ontylog 32
OOMediators 274
Open Knowledge Base Connectivity Protocol (OKBC) 297
Open Ontology Forge (OOF) 165
Orchestration 238
orchestration 272
Organization for the Advancement of Structured Information Standards (OASIS) 290
OWL 79, 118
OWL API 298
OWL based Metadata Framework 37
OWL Full 37, 100
OWL Lite 100
OWL Lite Aligner (OLA) 180
OWL Ontologies 82
OWL Rules Language (ORL) 124
OWL Rules Proposal 124
OWL-DL 32, 37, 100, 260
OWL-Lite 37
OWL-QL 73
OWL-S 259, 269, 303
PPAL 147
parallel branches 235
PARKA 191
Parmenides project 166
participant type 245
Pattern-based Annotation through Knowledge On the Web (PANKOW) 167
PDDL 282
Pellet 156
Petri nets 254
PICSEL 183, 187, 188
Planning Domain Description Language (PDDL) 261
postconditions 271
preconditions 271
Primitive datatypes 119
private processes 244, 245
Process mediation 274, 340
process mediation 284
process querying 277
Process Specification Language (PSL) 261
Process-Based Querying 280
professional annotators 162
PROMPT 151, 181
Properties 97
Property constraints 119
Property values 119
propositional satisfiability (SAT) 178
Protege 139
Protégé 147
Protocol mediation 274, 340
PSL-Core 301
PSL-Outer-Core 302
PSL-Outer-Core ontology 263
public processes 244, 245
QQ-Features 29
Query By Example (QBE) 51
Query Language 35
Query Languages 51
Query Languages for XML Data 51
Quick Ontology Mapping (QOM) 180
Quilt 54
Quinary 166
RRacer-Pro 122, 156
Rainbow 167
RDF 36
RDF based Metadata Framework 36
RDF Schema 79, 92, 118, 295
RDF Schema (RDFS) 36
RDF Schemas 32
RDQL62
receiver 199
receiving partner 199
receiving party 196
relationship type 245
Request Rewriting 278
request rewriting 277
Resource Description Framework (RDF) 35, 162, 261, 295
R-Features 29
role inclusions (RI) 155
role of sending and receiving 199
role type 245
Rosetta-Net210
RQL62
rule-based reasoning 187
Rule-ML 296
Rules Ontology for Web Services (ROWS) 262
SS-CREAM 164
Seeker 167
Semantic annotation 162
Semantic Annotations for WSDL (SAWSDL) 268
Semantic Correspondences 189
Semantic Web Rules Language (SWRL)156, 261, 296
Semantic Web Service Composition 281
Semantic Web Services 249
Semantic Web Services Framework (SWSF)261, 304
Semantic Web Services Initiative (SW SI) 292
Semantic Web Services Language (SWSL)261
Semantic Web Services Language for First Order Logic (SWSL-FOL) 262
Semantic Web Services Ontology (SWSO)261, 302
semantically corresponding objects 184
Semantics 35
Semantics and Web Services 226
semantics of information sources 183
Semantics of Web Services 249
Semantic Word 168
SemTag 167
Semtalk 141
sender 199
sending partner 199
sending party 196
Serialization Format 35
SeRQL 62
Service contracting 280
Service-Grounding 259
Service-Model 259
Service-Oriented Architecture (SOA) 215
Service-oriented Architecture (SOA)223
Service-Profile 259
Sesame 167
shared variable 196
shared vocabulary 184, 185
SHIF 155
SHIQ 156
SHIQ reasoner 155
SHOE 183, 188
SHOE Knowledge Annotator 165, 191
SHOIN(D) 156
Similarity Flooding (SF) 179
Simple Object Access Protocol 215
SIMS 183, 184, 186, 187, 188, 191
Single Ontology Approach 184
single ontology approach 184
Smart-Web project 166
S-Match 181
SMORE 165
SMTP 218
SNOMED17, 298
SOAP 215
SPARQL 36, 62, 65, 295
spatial registration 29
specification of a conceptualization 79
speech feature index 29
SROIQ(D) 156
Standard Generalized Markup Lan guage (SGML) 293
Standard Upper Ontology (SUO) 141
standardized formats 162
State-based Discovery 279
Statechart Diagrams 254
static composition 233
Statistical clustering 149
Structural Metadata 28
Structure Enrichment 188
Structure Resemblance 188
Structured Query Language (SQL) 54
Subclasses and properties 119
Subsumption-Based Discovery 278
subsumption-based matching 277
Suggested Upper Merged Ontology (SUMO) 177
SUPER 303
Supervised machine learning 148
surface Web 23
swimlanes 245
SWING 303
SWOOP 142
synchronous communication 195, 196
Systematized Nomenclature of Medicine (SNOMED) 155
TTAMBIS32, 187
Taxonomies 31
Taxonomy Based Disambiguation (TBD) 167
Teknowledge 164
Term Lists 31
Terminological Systems 79
Terminology 79
The Object Modeling Group (OMG) 291
Thesauri 31
Thesaurus 79
Thresher 168
topic change indices 29
Top-Level Grounding 189
top-level ontology 84, 189
traditional Web Services 216
transactional behavior 236
transactional control 236
transactional queueing 211
transactional RPC 211
Translation research 11
Translational Medicine 11
translational medicine 7
TRIPLE 62
TSIMMIS 183, 188
UUML models 82
UMLS Metathesaurus 32
Unified Medical Language System (UMLS) 300
Unified Modeling Language (UML) 297
Union Types 90
United States National Library of Medicine (NLM) 292
Universal Description Discovery and Integration (UDDI) 216
Upper Ontologies 84
VVannotea 164, 165
Versa 62
Visual Ontology Modeler 141
Vocabularies and Reference Terms for Metadata 30
Vocabulary 79
WW3C Semantic Annotations for the Web Services Description Language (SAWSDL)302
Web Ontology Language (OWL) 32, 35, 82, 162, 259, 296, 303
Web Service 270
Web Service Choreography Description Language (WS-CDL) 245
Web Service Composition 233
Web Service composition 237
Web Service Description Language (WSDL)216
Web Service Interoperability Organization (WS-I) 227
Web Service Invocation Framework (WSIF) 238
Web Service Model Execution (WSMX) 303
Web Service Modeling Execution Environment (WSMX) 275
Web Service Modeling Language (WSML)116
Web Service Modeling Languge (WSML) 303
Web Service Standards 221
Web Service Technology Stack 221
Web Services BPEL Technical Committee 244
Web Services Business Process Execution Language (WS-BPEL) 244
Web Services Business Process Execution Language (WSBPEL) 283
Web Services Modeling Framework 303
Web Services Modeling Ontology (WSMO) 303
Web Services Modeling Toolkit (WSMT) 276
WebODE 139, 147
WebOnto 140, 147
WGMediators 274
WiCKOffice 168
Word-Net 176
Workflow and Business Processes Technology 282
World Wide Web Consortium (W3C) 290
WS*-Stack220
WS-CDL 222
WSDL 244
WSDL-S 266, 304
WSFL 244
WSIF 224, 244
WSIL 222
WSML-Core 11 7
WSML-DL 117
WSML-Flight 11 7
WSML-Full 117
WSML-Rule 11 7
WSMO 269
WSMO Studio 276
WSM04JParser 275
WSMX Source-Forge Project 276
WWMediator 274
XXBQE 52
XLANG 244
XLink 36
XML based Metadata Framework 36
XML document 84
XML RPC 215
XML Schema 32, 79, 84, 118, 294
XML-GL 51
XML-QL 51, 54
XPath 36, 54, 244, 294
XPointer36, 164
XQL 52, 54
XQuery 36, 52, 54, 294
XSL Formatting Objects (XSL/FO) 36
XSL transformations (XSLT) 36
XSLT 51, 244
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 eight international conferences.
"Kashyap et al. (...) provide an organized and well-written textbook that can serve as both a theoretical guide and a practical tutorial for the informational and computational aspects of the Semantic Web." Athena Vakali in ACM Reviews February 2009