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