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Information Sharing on the Semantic Web

:	Heiner Stuckenschmidt, Frank van Harmelen
:	Information Sharing on the Semantic Web
:	Springer-Verlag
:	9783540269076
:	1
:	CHF 85.40
:

:	Informatik
:	English

:	278
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

Details recent research in areas such as ontology design for information integration, metadata generation and management, and representation and management of distributed ontologies.

Provides decision support on the use of novel technologies, information about potential problems, and guidelines for the successful application of existing technologies.

Heiner Stuckenschmidt holds a post-doc position in the Knowledge Representation and Reasoning Group at the Vrije Universiteit Amsterdam where he received his PhD for work on Ontology-Based Information Sharing on the Semantic Web. His works include Semantic Web related topics such as ontology languages, knowledge-based meta data management and robust and scalable terminological reasoning. Before moving to Amsterdam, he was employed as a researcher and lecturer at the University of Bremen. His research activities in Bremen included the application of ontologies for information sharing in web based information systems with a special focus on semantics-preserving information integration and spatially related information.

He is organizer of a series of workshops on ontologies at international conferences (IJCAI'01, ECAI'02, IJCAI'03) and member of program committees of several semantic web related conferences (SWWS'01, ISWC'02, WWW'03) and has held / will hold tutorial on the topic of the proposed book at different conferences (K-CAP 2001, IJCAI'03, ISWC'03). He is editor of a book on the application of ontologies in the cadastral domain and has published more than 40 paper in international journals, conferences and workshops.

Frank van Harmelen is professor in Knowledge Representation and Reasoning at the Department of Artificial Intelligence of the Vrije Universiteit Amsterdam. He was awarded a PhD from the Department of AI in Edinburgh for his research on meta-level reasoning, after having studied Mathematics and Computer Science in Amsterdam. He is author of a book on meta-level inference, editor of a book on knowledge-based systems, editor of a book on Knowledge Management on the Semantic Web, and is currently preparing a text-book on Semantic Web languages. He has published over 100 papers, many of them in leading journals and conferences. He has made key contributions to the CommonKADS project by providing a formal basis for the conceptual models. More recently, he has been co-projectmanager of the On-To-Knowledge project, and was one of the designers of OIL, which (in its form DAML +OIL) is currently the basis for a W3C standardized Web ontology language.

He is a member of the joint EU/US committee on agent markup languages (who designed DAML+OIL), and is an active member of the W3C working group on Web Ontology languages, responsible for the OWL Web Ontology Language. He was the 2002 Program Chair of the European Conference on Artificial Intelligence, and will be the General Chair of the 2004 International Semantic Web Conference.

	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