Stuckenschmidt / Harmelen Information Sharing on the Semantic Web

1. Auflage 2005
ISBN: 978-3-540-26907-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 278 Seiten, eBook

Reihe: Advanced Information and Knowledge Processing

The large-scale and almost ubiquitous availability of information has become as much of a curse as it is a blessing. The more information is available, the harder it is to locate any particular piece of it. And even when it has been successfully found, it is even harder still to usefully combine it with other information we may already possess.

It is commonly understood that this problem of information sharing can only be solved by giving computers better access to the semantics of the information. While it has been recognized that ontologies play a crucial role in solving the open problems, most approaches rely on the existence of well-established data structures. To overcome these shortcomings, Stuckenschmidt and van Harmelen describe ontology-based approaches for resolving semantic heterogeneity in weakly structured environments, in particular the World Wide Web. Addressing problems like missing conceptual models, unclear system boundaries, and heterogeneous representations, they design a framework for ontology-based information sharing in weakly structured environments like the Semantic Web.

For researchers and students in areas related to the Semantic Web, the authors provide not only a comprehensive overview of the State of the art, but also present in detail recent research in areas like ontology design for information integration, metadata generation and management, and representation and management of distributed ontologies. For professionals in areas such as e-commerce and knowledge management, the book provides decision support on the use of novel technologies, information about potential problems, and guidelines for the successful application of existing technologies.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Stuckenschmidt, Heiner

Harmelen, Frank van

Inhaltsverzeichnis

1;Preface;6
1.1;About the book;6
1.1.1;The success of the information society;6
1.1.2;The remaining problems;7
1.1.3;Intended readership;9
1.2;Organization of the Book;9
1.3;Acknowledgements;11
2;Contents;13
3;Part I Information sharing and ontologies;18
3.1;1 Semantic integration;19
3.1.1;1.1 Syntactic standards;20
3.1.1.1;1.1.1 HTML: visualizing information;20
3.1.1.2;1.1.2 XML: exchanging information;21
3.1.1.3;1.1.3 RDF: a data model for meta-information;22
3.1.1.4;1.1.4 The roles of XML and RDF;24
3.1.2;1.2 The Problem of Heterogeneity;26
3.1.2.1;1.2.1 Structural Conflicts;26
3.1.2.2;1.2.2 Semantic Conflicts;28
3.1.3;1.3 Handling information semantics;30
3.1.3.1;1.3.1 Semantics from structure;31
3.1.3.2;1.3.2 Semantics from text;32
3.1.3.3;1.3.3 The need for explicit semantics;33
3.1.4;1.4 Representing and comparing semantics;35
3.1.4.1;1.4.1 Names and labels;36
3.1.4.2;1.4.2 Term networks;36
3.1.4.3;1.4.3 Concept lattices;37
3.1.4.4;1.4.4 Features and constraints;38
3.1.5;1.5 Conclusion;39
3.1.5.1;Further Reading;39
3.2;2 Ontology-based information sharing;40
3.2.1;2.1 Ontologies;40
3.2.1.1;2.1.1 Shared vocabularies and conceptualizations;41
3.2.1.2;2.1.2 Speci.cation of context knowledge;42
3.2.1.3;2.1.3 Beneficial applications;44
3.2.2;2.2 Ontologies in information integration;46
3.2.2.1;2.2.1 Content explication;46
3.2.2.2;2.2.2 Additional roles of ontologies;49
3.2.3;2.3 A framework for information sharing;51
3.2.4;2.4 A translation approach to ontology alignment;53
3.2.4.1;2.4.1 The translation process;54
3.2.4.2;2.4.2 Required infrastructure;55
3.2.5;2.5 Conclusions;57
3.3;3 Ontology languages for the Semantic Web;60
3.3.1;3.1 An abstract view;60
3.3.2;3.2 Two Semantic Web ontology languages;62
3.3.2.1;3.2.1 RDF Schema;64
3.3.2.2;3.2.2 OWL Lite;65
3.3.2.3;3.2.3 OWL DL;67
3.3.2.4;3.2.4 OWL Full;68
3.3.2.5;3.2.5 Computational Complexity;69
3.3.2.6;3.2.6 Simple relations between ontologies;69
3.3.3;3.3 Other Web-based ontology languages;73
3.3.3.1;3.3.1 Languages for expressing ontology mappings;75
3.3.4;3.4 Conclusions;76
4;Part II Creating ontologies and metadata;77
4.1;4 Ontology creation;78
4.1.1;4.1 Ontological engineering;79
4.1.2;4.2 Building an ontology infrastructure for Information sharing;81
4.1.3;4.3 Applying the approach;83
4.1.3.1;4.3.1 The task to be solved;84
4.1.3.2;4.3.2 The Information Sources;85
4.1.3.3;4.3.3 Sources of knowledge;86
4.1.4;4.4 An example walkthrough;89
4.1.5;4.5 Conclusions;95
4.2;5 Metadata generation;97
4.2.1;5.1 The role of metadata;98
4.2.1.1;5.1.1 Use of metadata;99
4.2.1.2;5.1.2 Problems with metadata management;100
4.2.2;5.2 The WebMaster approach;102
4.2.2.1;5.2.1 BUISY: A Web based environmental information system;102
4.2.2.2;5.2.2 The WebMaster Workbench;103
4.2.2.3;5.2.3 Applying WebMaster to the BUISY system;105
4.2.3;5.3 Learning classification rules;109
4.2.3.1;5.3.1 Inductive logic programming;110
4.2.3.2;5.3.2 Applying inductive logic programming;112
4.2.3.3;5.3.3 Learning experiments;114
4.2.3.4;5.3.4 Extracted classi.cation rules;118
4.2.4;5.4 Ontology deployment;122
4.2.4.1;5.4.1 Generating ontology-based metadata;123
4.2.4.2;5.4.2 Using ontology-based metadata;124
4.2.5;5.5 Conclusions;126
5;Part III Retrieval, integration and querying;128
5.1;6 Retrieval and Integration;129
5.1.1;6.1 Semantic integration;130
5.1.1.1;6.1.1 Ontology heterogeneity;130
5.1.1.2;6.1.2 Multiple systems and translatability;132
5.1.1.3;6.1.3 Approximate re-classification;133
5.1.2;6.2 Concept-based filtering;135
5.1.2.1;6.2.1 The idea of query-rewriting;136
5.1.2.2;6.2.2 Boolean concept expressions;137
5.1.2.3;6.2.3 Query re-writing;139
5.1.3;6.3 Processing complex queries;141
5.1.3.1;6.3.1 Queries as concepts;142
5.1.3.2;6.3.2 Query relaxation;144
5.1.4;6.4 Examples from a case study;147
5.1.4.1;6.4.1 Concept approximations;147
5.1.4.2;6.4.2 Query relaxation;148
5.1.5;6.5 Conclusions;150
5.2;7 Sharing statistical information;152
5.2.1;7.1 The nature of statistical information;153
5.2.1.1;7.1.1 Statistical metadata;154
5.2.1.2;7.1.2 A basic ontology of statistics;155
5.2.2;7.2 Modelling Statistics;159
5.2.2.1;7.2.1 Statistics as views;159
5.2.2.2;7.2.2 Connection with the domain;160
5.2.3;7.3 Translation to Semantic Web languages;164
5.2.3.1;7.3.1 Ontologies;164
5.2.3.2;7.3.2 Description of information;168
5.2.4;7.4 Retrieving statistical information;171
5.2.5;7.5 Conclusions;173
5.3;8 Spatially-related information;175
5.3.1;8.1 Spatial representation and reasoning;176
5.3.1.1;8.1.1 Levels of spatial abstraction;176
5.3.1.2;8.1.2 Reasoning about spatial relations;177
5.3.2;8.2 Ontologies and spatial relevance;178
5.3.2.1;8.2.1 Defining Spatial Relevance;179
5.3.2.2;8.2.2 Combined spatial and terminological matching;180
5.3.2.3;8.2.3 Limitations;182
5.3.3;8.3 Graph-based reasoning about spatial relevance;183
5.3.3.1;8.3.1 Partonomies;184
5.3.3.2;8.3.2 Topology;186
5.3.3.3;8.3.3 Directions;187
5.3.3.4;8.3.4 Distances;188
5.3.4;8.4 Conclusions;190
5.4;9 Integration and retrieval systems;192
5.4.1;9.1 OntoBroker;193
5.4.1.1;9.1.1 F-Logic and its relation to OWL;194
5.4.1.2;9.1.2 Ontologies, sources and queries;196
5.4.1.3;9.1.3 Context transformation;198
5.4.2;9.2 OBSERVER;199
5.4.2.1;9.2.1 Query Processing in OBSERVER;200
5.4.2.2;9.2.2 Vocabulary integration;202
5.4.2.3;9.2.3 Query plan generation and selection;204
5.4.3;9.3 The BUSTER system;205
5.4.3.1;9.3.1 The use of shared vocabularies;207
5.4.3.2;9.3.2 Retrieving accommodation information;208
5.4.3.3;9.3.3 Spatial and temporal information;210
5.4.4;9.4 Conclusions;214
6;Part IV Distributed ontologies;215
6.1;10 Modularization;216
6.1.1;10.1 Motivation;217
6.1.1.1;10.1.1 Requirements;218
6.1.1.2;10.1.2 Our approach;218
6.1.1.3;10.1.3 Related work;219
6.1.2;10.2 Modular ontologies;221
6.1.2.1;10.2.1 Syntax and architecture;221
6.1.2.2;10.2.2 Semantics and logical consequence;222
6.1.3;10.3 Comparison with OWL;225
6.1.3.1;10.3.1 Simulating OWL import;225
6.1.3.2;10.3.2 Beyond OWL;228
6.1.4;10.4 Reasoning in modular ontologies;230
6.1.4.1;10.4.1 Atomic concepts and relations;230
6.1.4.2;10.4.2 Preservation of Boolean operators;230
6.1.4.3;10.4.3 Compilation and integrity;232
6.1.5;10.5 Conclusions;233
6.2;11 Evolution management;236
6.2.1;11.1 Change detection and classification;237
6.2.1.1;11.1.1 Determining harmless changes;237
6.2.1.2;11.1.2 Characterizing changes;238
6.2.1.3;11.1.3 Update management;240
6.2.2;11.2 Application in a case study;241
6.2.2.1;11.2.1 The WonderWeb case study;241
6.2.2.2;11.2.2 Modularization in the case study;243
6.2.2.3;11.2.3 Updating the models;244
6.2.3;11.3 Conclusions;245
7;Part V Conclusions;247
7.1;12 Conclusions;248
7.1.1;12.1 Lessons learned;248
7.1.2;12.2 Assumptions and Limitations;251
7.1.2.1;12.2.1 Shared Vocabularies;251
7.1.2.2;12.2.2 On demand translation;252
7.1.2.3;12.2.3 Modular Ontologies;253
7.1.3;12.3 Where are we now?;254
7.1.4;12.4 Is that all there is?;255
8;A Proofs of theorems;258
8.1;A.1 Theorem 6.6;258
8.2;A.2 Theorem 6.11;258
8.3;A.3 Theorem 6.14;259
8.4;A.4 Theorem 10.9;259
8.5;A.5 Theorem 10.11;259
8.6;A.6 Lemma 11.1;262
8.7;A.7 Theorem 11.2;262
9;References;263
10;Index;277