Poli / Healy / Kameas Theory and Applications of Ontology: Computer Applications

1. Auflage 2010
ISBN: 978-90-481-8847-5
Verlag: Springer Netherlands
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 576 Seiten

Ontology was once understood to be the philosophical inquiry into the structure of reality: the analysis and categorization of 'what there is'. Recently, however, a field called 'ontology' has become part of the rapidly growing research industry in information technology. The two fields have more in common than just their name.

Theory and Applications of Ontology is a two-volume anthology that aims to further an informed discussion about the relationship between ontology in philosophy and ontology in information technology. It fills an important lacuna in cutting-edge research on ontology in both fields, supplying stage-setting overview articles on history and method, presenting directions of current research in either field, and highlighting areas of productive interdisciplinary contact.

Theory and Applications of Ontology: Computer Applications presents ontology in ways that philosophers are not likely to find elsewhere. The volume offers an overview of current research in ontology, distinguishing basic conceptual issues, domain applications, general frameworks, and mathematical formalisms. It introduces the reader to current research on frameworks and applications in information technology in ways that are sure to invite reflection and constructive responses from ontologists in philosophy.

Roberto Poli (B.A. in sociology, with honors, Ph.D. on ontology for knowledge engineers, Utrecht) is editor-in-chief of Axiomathes (Springer), a peer-reviewed academic journal devoted to the study of ontology and cognitive systems, editor of Categories (Ontos), and member of the Academic Board of Directors of the Metanexus Institute, Philadelphia. His research interests include (1) ontology, in both its traditional philosophical understanding and the new, computer-oriented, understanding, (2) the theory of values and the concept of person and (3) anticipatory systems, i.e. system able to take decisions according to their possible future development. Poli has published four books, edited or co-edited more than 20 books or journal's special issues and published more than 150 scientific papers. He teaches Applied Ethics and Futures Studies at the Faculty of Sociology and gives a course in Ontology at the Faculty of Literature and Philosophy, University of Trento.
Michael J. Healy received a B.A degree in mathematics from Eastern Washington University at Cheney, Washington in 1965 and a M.S. in mathematics from the University of Idaho in 1967. From 1967 through 2001 he worked for The Boeing Company, first as a consultant in nonlinear programming and, beginning in 1989, in research. His research spanned neural networks, machine learning, formal verification, and applications of category theory in software synthesis, knowledge based systems (KBS) engineering (KBSE), and knowledge representation and ontologies for KBS interoperability. He is now a Senior Research Scholar in the Electrical and Computer Engineering Department (ECE) at the University of New Mexico, which he joined in 2000. He continues to pursue his research interests in the semantics of neural networks, cognitive neuroscience, knowledge representation, and ontologies for systems, including computational, cognitive, and social systems. Category theory is the central ma thematical discipline for his research, with a particular focus upon categorical logic and model theory.
Achilles D. Kameas received his Engineering Diploma (in 1989) and his Ph.D. (in 1995, in Human-Computer Interaction), both from the Department of Computer Engineering and Informatics, Univ. of Patras, Greece. Since 2003, he is an Assistant Professor with the Hellenic Open University, where he teaches software design and engineering. He is also the Director of Research Unit 3 / DAISy (Designing Ambient Intelligent Systems) (http://daisy.cti.gr) at the Research Academic Computer Technology Institute (CTI). Since 2007 he is Deputy Dean of the School of Sciences and Technology (SST) of the Hellenic Open University and Director of the e-Comet Lab (Educational Content, Methodologies and Technologies Lab) (http://eeyem.eap.gr). He has participated as researcher, engineer, group leader or scientific coordinator in several EU R&D projects, such as e-Gadgets, Plants, Social, Astra and Atraco. He has published over 100 journal articles, conference papers and book chapters, authored three university textbooks and co-edited more than five books.He is a member of the Advisory Board of Panorama CA and the scientific committee of the Intelligent Environments conferences; in the past he was elected in the steering boards of the Disappearing Computer network and Convivio network. His current research interests include architectures, languages and tools for ubiquitous computing systems, engineering of ubiquitous computing applications, and engineering and application of ontologies and ontology matching. He is a voting member of IEEE, IEEE CS, ACM and ACM SIGCHI. He is a member of Technical Chamber of Greece, Hellenic AI Society and Hellenic Society for the application of ICT in Education.

Autoren/Hrsg.

Poli, Roberto

Healy, Michael

Kameas, Achilles

Inhaltsverzeichnis

1;Preface;4
2;Contents;8
3;Contributors;10
4;Introduction;13
5;1 The Interplay Between Ontology as Categorial Analysis and Ontology as Technology;17
5.1;1.1 Introduction;17
5.2;1.2 Ontology_c;18
5.3;1.3 Ontology_t;20
5.3.1;1.3.1 Ontology_t Definitions;20
5.3.2;1.3.2 Ontology_t and Epistemology;21
5.3.3;1.3.3 Ontology_t as Theory with Philosophical Stances;22
5.4;1.4 Interplay Between Ontologyc and Ontologyt;23
5.4.1;1.4.1 Developing Formalized Ontologies;24
5.4.2;1.4.2 Ontology, Science, and Levels of Reality;28
5.4.3;1.4.3 Example: An Ontology of Biology;30
5.5;1.5 Looking Toward the Future;34
5.5.1;1.5.1 Better Ordering Relations for Ontologies;34
5.5.2;1.5.2 Elaboration of the Distinctions Among Ontology Levels;35
5.5.3;1.5.3 Ontology Modularity, Mapping, and Formalization of Context;36
5.5.4;1.5.4 Representation vs. Reasoning;37
5.5.5;1.5.5 Final Words;38
5.6;1.6 Acknowledgments and Disclaimers;38
5.7;References;38
6;2 Ontological Architectures;43
6.1;2.1 Introduction;43
6.2;2.2 Ontological and Ontology Architecture: Overview;44
6.2.1;2.2.1 Truth and Belief: Ontology, Epistemology, Contextual Semantics, Language, and Applications;44
6.2.2;2.2.2 The Big Picture;45
6.2.3;2.2.3 The Ontology Spectrum;46
6.2.4;2.2.4 The Ontology Maturity Model;51
6.3;2.3 Ontological Architecture: Upper, Mid-level, Domain Ontologies;52
6.3.1;2.3.1 What Is an Upper Ontology?;53
6.3.1.1;2.3.1.1 Upper Ontology Definition;53
6.3.1.2;2.3.1.2 Upper Ontology vs. Mid-Level Ontology;54
6.3.1.3;2.3.1.3 Upper Ontology vs. Domain Ontology;54
6.3.2;2.3.2 Why Do We Care About Upper Ontology?;54
6.3.2.1;2.3.2.1 How Upper Ontologies May Help;54
6.3.2.2;2.3.2.2 A Software Engineer Analogy;55
6.3.3;2.3.3 What Foundational Ontologies Provide: Ontological Choices;56
6.3.3.1;2.3.3.1 Descriptive vs. Revisionary;56
6.3.3.2;2.3.3.2 Multiplicative vs. Reductionist;57
6.3.3.3;2.3.3.3 Universals, Particulars, Sets, Possible Worlds;57
6.3.3.4;2.3.3.4 Endurants and Perdurants;59
6.3.4;2.3.4 Upper Ontology Initiatives and Candidates;60
6.4;2.4 Structuring the Ontological and Meta-Ontological Space;61
6.4.1;2.4.1 Knowledge Representation Languages and Meta-Ontologies;61
6.4.2;2.4.2 The Lattice of Theories;65
6.4.3;2.4.3 Modularity and Context in the Ontological Space;66
6.4.4;2.4.4 Microtheories, Little Theories, Ontology Versioning;68
6.4.5;2.4.5 Information Flow Framework Meta-Ontology;70
6.5;2.5 What the Future Holds: A Vision;72
6.6;References;75
7;3 Organization and Management of Large Categorical Systems;83
7.1;3.1 Introduction;83
7.2;3.2 Terminological Systems in Medicine;84
7.2.1;3.2.1 Compositionality;85
7.2.2;3.2.2 Navigation;87
7.3;3.3 Complex Systems and Modularization in General;88
7.4;3.4 Abstract Framework for Modules;89
7.4.1;3.4.1 Overview;90
7.4.2;3.4.2 Formal Preliminaries;91
7.4.3;3.4.3 Defining Modules;91
7.4.4;3.4.4 Example Module Types;94
7.4.4.1;3.4.4.1 Basic Modules;94
7.4.4.2;3.4.4.2 Modules in Distributed First Order Logic;95
7.5;3.5 Characteristics of Module Notions;95
7.5.1;3.5.1 Informal Characteristics;95
7.5.2;3.5.2 Formal Characteristics;96
7.5.2.1;3.5.2.1 Characteristics Primarily Based on Either Interfaces, Modules or Systems;96
7.5.2.2;3.5.2.2 Characteristics with Respect to the Interplay of Modules and Systems;97
7.5.3;3.5.3 Discussion of Characteristics;98
7.6;3.6 Analytic Overview of Logical Approaches;99
7.6.1;3.6.1 Conservativity and Disjoint Languages;100
7.6.2;3.6.2 Partition-Based Reasoning;101
7.6.3;3.6.3 Semantic Encapsulation;102
7.6.4;3.6.4 Package-based Description Logics;103
7.6.5;3.6.5 Distributed Logics;103
7.6.6;3.6.6 Summarizing Overview;105
7.7;3.7 Concluding Remarks;107
7.7.1;3.7.1 Further Related Areas;107
7.7.2;3.7.2 Conclusions;108
7.8;References;109
8;4 The Information Flow Approach to Ontology-Based Semantic Alignment;117
8.1;4.1 Introduction;117
8.2;4.2 Ontology-Based Semantic Integration: Basic Concepts and Definitions;118
8.2.1;4.2.1 Semantic Matching;119
8.2.2;4.2.2 Integration Theory;120
8.2.3;4.2.3 Semantic Alignment;121
8.3;4.3 Semantic Alignment Through Meaning Coordination;122
8.4;4.4 Semantic Alignment Hypotheses;123
8.5;4.5 Applications and Explorations;126
8.6;4.6 Conclusions;128
8.7;References;129
9;5 Ontological Evaluation and Validation;131
9.1;5.1 Introduction;131
9.2;5.2 Current Approaches in Ontology Evaluation and Validation;133
9.2.1;5.2.1 Evolution-Based;133
9.2.2;5.2.2 Logical (Rule-Based);134
9.2.3;5.2.3 Metric-Based (Feature-Based);135
9.3;5.3 OntoQA: Metric-Based Ontology Quality Analysis;137
9.3.1;5.3.1 Schema Metrics;138
9.3.1.1;5.3.1.1 Relationship Richness;138
9.3.1.2;5.3.1.2 Inheritance Richness;139
9.3.1.3;5.3.1.3 Attribute Richness;139
9.3.2;5.3.2 Knowledgebase Metrics;139
9.3.2.1;5.3.2.1 Class Richness;140
9.3.2.2;5.3.2.2 Class Connectivity;140
9.3.2.3;5.3.2.3 Class Importance;140
9.3.2.4;5.3.2.4 Cohesion;141
9.3.2.5;5.3.2.5 Relationship Richness;141
9.3.3;5.3.3 OntoQA Results;141
9.4;5.4 Conclusion;144
9.5;References;144
10;6 Tools for Ontology Engineering and Management;147
10.1;6.1 Introduction;147
10.2;6.2 Classification of Ontology Tools;148
10.2.1;6.2.1 Specialized Ontology Engineering Tools;148
10.2.1.1;6.2.1.1 Ontology Engineering Tools;148
10.2.1.2;6.2.1.2 Ontologies Combination Tools;152
10.2.1.3;6.2.1.3 Ontology Management Tools;156
10.2.2;6.2.2 Integrated Ontology Engineering Environments;161
10.3;6.3 Selecting the Appropriate Ontology Engineering And Management Tool;163
10.4;6.4 Conclusion;165
10.5;References;166
11;7 Ontological Tools: Requirements, Design Issues and Perspectives;171
11.1;7.1 Introduction;171
11.2;7.2 The Engineering of Ontologies;173
11.2.1;7.2.1 The HCOME Methodology;175
11.2.1.1;7.2.1.1 Specification Phase;176
11.2.1.2;7.2.1.2 Conceptualization Phase;176
11.2.1.3;7.2.1.3 Exploitation Phase;177
11.2.2;7.2.2 The DILIGENT Methodology;177
11.3;7.3 Next-Generation Ontology Engineering Tools;179
11.4;7.4 Supporting Ontology Engineering;183
11.4.1;7.4.1 Integrated O.E Environments;183
11.4.2;7.4.2 Self-Standing O.E Tools;184
11.5;7.5 Conclusion;185
11.6;References;188
12;8 Using the Unified Foundational Ontology (UFO) as a Foundation for General Conceptual Modeling Languages;190
12.1;8.1 Introduction;190
12.2;8.2 The Unified Foundational Ontology (UFO);191
12.2.1;8.2.1 The Core Categories: Object--Object Universal, Moment--Moment Universal;191
12.2.2;8.2.2 Qualities, Qualia and Modes;193
12.2.3;8.2.3 Relations, Relators and Qua Individuals;195
12.2.4;8.2.4 Object Universals;198
12.3;8.3 A Framework for Language Evaluation and (Re)Design;200
12.4;8.4 Evaluating and Redesigning the UML 2.0 Metamodel;203
12.5;8.5 Reinforcing the Isomorphism Between UFO and UML;206
12.6;8.6 Final Considerations;209
12.7;References;210
13;9 Lightweight Ontologies;212
13.1;9.1 Introduction;212
13.2;9.2 Lightweight Ontologies;215
13.2.1;9.2.1 Lightweight Ontologies and the Semantic Spectrum;215
13.2.2;9.2.2 Folksonomies and Lightweight Ontologies;218
13.2.3;9.2.3 Thesauri and Lightweight Ontologies;219
13.2.4;9.2.4 Formal Classification and Lightweight Ontologies;219
13.3;9.3 Ontologies and the Semantic Web;219
13.4;9.4 Ontologies and Information Integration;223
13.5;9.5 Ontologies and Knowledge Management;226
13.5.1;9.5.1 Limitations of Current Technology;227
13.5.2;9.5.2 Applying Ontologies in Knowledge Management;229
13.5.3;9.5.3 Semantic Knowledge Management Tools;231
13.5.3.1;9.5.3.1 Squirrel Semantic Search Engine;231
13.6;9.6 Ontologies and Service-Oriented Environments;234
13.6.1;9.6.1 Web Service Modeling Ontology (WSMO);236
13.6.2;9.6.2 Web Service Modeling Language (WSML);237
13.6.3;9.6.3 Web Service Modeling Execution Environment (WSMX);238
13.7;9.7 Ontologies and Computer Science;239
13.8;9.8 Conclusion;240
13.9;References;241
14;10 WordNet;245
14.1;10.1 Introduction;245
14.2;10.2 Design and Contents;246
14.3;10.3 Coverage;246
14.4;10.4 Relations;246
14.5;10.5 Nouns in WordNet;247
14.5.1;10.5.1 Hyponymy;247
14.5.2;10.5.2 Types vs. Instances;248
14.5.3;10.5.3 Meronymy;248
14.6;10.6 Verbs;248
14.7;10.7 Adjectives;249
14.8;10.8 Where do Relations Come from?;249
14.9;10.9 WordNet as a Thesaurus;250
14.10;10.10 Semantic Distance and Lexical Gaps;250
14.11;10.11 WordNet as an Ontology;251
14.12;10.12 WordNet and Formal Ontology;251
14.13;10.13 Wordnets in Other Languages;252
14.14;10.14 The EuroWordNet Model;252
14.15;10.15 Global WordNets;254
14.16;10.16 WordNet as a Tool for Natural Language Processing;254
14.17;10.17 Conclusions;255
14.18;References;255
15;11 Controlled English to Logic Translation;258
15.1;11.1 Introduction;258
15.2;11.2 WordNet Mappings;260
15.3;11.3 Simple Parsing and Interpretation;261
15.3.1;11.3.1 Word Sense Disambiguation;262
15.4;11.4 Issues in Translation;263
15.4.1;11.4.1 Case Roles and Word Order;263
15.4.2;11.4.2 Statives;264
15.4.3;11.4.3 Attributes;264
15.4.4;11.4.4 Counting;265
15.4.5;11.4.5 Copula Expressions;265
15.4.6;11.4.6 Prepositions;265
15.4.7;11.4.7 Quantification;266
15.4.8;11.4.8 Possessives;267
15.4.9;11.4.9 Anaphor;268
15.4.10;11.4.10 Conjunction and Disjunction;269
15.4.11;11.4.11 Negation;269
15.5;11.5 CELT Components;270
15.6;References;270
16;12 Cyc;272
16.1;12.1 Introduction;272
16.1.1;12.1.1 The Form of the Language;273
16.1.2;12.1.2 Vocabulary;273
16.1.3;12.1.3 OpenCyc and ResearchCyc;274
16.2;12.2 Upper Ontology;275
16.2.1;12.2.1 Higher Order Classes;277
16.3;12.3 Contexts;278
16.3.1;12.3.1 Dimensions of Context Space;279
16.3.2;12.3.2 Vocabulary/Theory/Data Contexts;279
16.3.3;12.3.3 Spindles;280
16.3.4;12.3.4 Problem Solving Contexts;281
16.3.5;12.3.5 Hypothetical Contexts;281
16.3.6;12.3.6 Fictional Contexts;281
16.3.7;12.3.7 UniversalVocabularyMt;282
16.4;12.4 Functions;282
16.4.1;12.4.1 Prototypes;283
16.4.2;12.4.2 Skolemization;284
16.5;12.5 Reasoning;284
16.5.1;12.5.1 Forward and Backward Chaining;284
16.5.2;12.5.2 Don't Care Variables;285
16.5.3;12.5.3 Rule Macro Predicates;285
16.5.4;12.5.4 Monotonic vs. Default Reasoning;286
16.5.5;12.5.5 Exceptions to Rules;286
16.6;12.6 Events;287
16.7;12.7 Conceptual Works;287
16.8;12.8 Open/Closed World Assumption;288
16.9;12.9 Geopolitical Entities;288
16.10;12.10 Temporal Reasoning;289
16.11;12.11 Natural Language Support;289
16.12;12.12 Cyc and the Semantic Web;290
16.13;12.13 Summary;291
16.14;References;291
17;13 Ontological Foundations of DOLCE;292
17.1;13.1 Introduction;292
17.2;13.2 A Bit of History;293
17.3;13.3 Ontological vs. Conceptual Level;294
17.4;13.4 Properties;295
17.5;13.5 Basic Categories;298
17.6;13.6 Parthood;298
17.7;13.7 Time;299
17.8;13.8 Temporary Parthood;301
17.9;13.9 Concepts;302
17.10;13.10 Qualities and Locations;302
17.11;13.11 Objects and Events;304
17.12;References;308
18;14 General Formal Ontology (GFO): A Foundational Ontology for Conceptual Modelling;309
18.1;14.1 Introduction;309
18.2;14.2 Basic Assumptions and Logical Methods;312
18.2.1;14.2.1 Philosophical Assumptions;312
18.2.2;14.2.2 Concepts, Symbols, and Universals;313
18.2.3;14.2.3 The Axiomatic Method;314
18.2.4;14.2.4 Representation of Ontologies;315
18.2.5;14.2.5 Types of Realism;315
18.2.6;14.2.6 Levels of Reality;317
18.3;14.3 Meta-Ontological Architecture of GFO;318
18.4;14.4 The Basic Categories of Individuals of GFO;319
18.4.1;14.4.1 Space-Time;320
18.4.2;14.4.2 Principal Distinctions;321
18.4.3;14.4.3 Material Structures Material Structure;322
18.4.4;14.4.4 Processual Complexes, Processes, and Occurrents;324
18.4.4.1;14.4.4.1 Processual Complexes;325
18.4.4.2;14.4.4.2 Processes;325
18.4.4.3;14.4.4.3 Occurrents;327
18.4.4.4;14.4.4.4 Basic Classification of Processes;329
18.4.5;14.4.5 Attributives;331
18.4.5.1;14.4.5.1 Properties;331
18.4.5.2;14.4.5.2 Relations and Roles;333
18.4.5.3;14.4.5.3 Functions;336
18.4.6;14.4.6 Facts, Propositions, and Situations;338
18.5;14.5 Basic Relations of GFO;341
18.5.1;14.5.1 Existential Dependency;341
18.5.2;14.5.2 Set and Set-Theoretical Relations;342
18.5.3;14.5.3 Instantiation and Categories;342
18.5.4;14.5.4 Property Relations and Relators;343
18.5.5;14.5.5 Property Bearer Parthood Relation;343
18.5.6;14.5.6 Boundaries, Coincidence, and Adjacence;344
18.5.7;14.5.7 Relations of Concrete Individuals to Space and Time;345
18.5.8;14.5.8 Participation;345
18.5.9;14.5.9 Association;346
18.5.10;14.5.10 Ontical Connectedness and Causality;346
18.6;14.6 Object-Process Integration;347
18.6.1;14.6.1 Processual Unification and Cognition;347
18.6.2;14.6.2 Completed Categories and Integrated Individuals;348
18.6.3;14.6.3 Comparison to Other 4D-Ontologies;349
18.7;14.7 Principles of Ontology Development and Ontological Modelling;350
18.7.1;14.7.1 Domains and Conceptualizations;350
18.7.2;14.7.2 Steps of Ontology Development;351
18.7.3;14.7.3 Ontological Modelling;353
18.8;References;354
19;15 Ontologies in Biology;358
19.1;15.1 Introduction;358
19.2;15.2 Ontologies in Biomedicine;360
19.2.1;15.2.1 The Open Biomedical Ontologies;360
19.2.2;15.2.2 The Gene Ontology;363
19.2.3;15.2.3 Ontology Representation;363
19.2.4;15.2.4 Ontology Curation;366
19.2.5;15.2.5 Annotation;366
19.3;15.3 Criticism and Extension of the Gene Ontology;368
19.4;15.4 Biomedical Ontology Integration Through the Application of Ontological Design Principles;370
19.4.1;15.4.1 The OBO Relationship Ontology;371
19.4.2;15.4.2 BioTop and the Simple Bio Upper Ontology;371
19.4.3;15.4.3 GFO-Bio;372
19.4.4;15.4.4 Defaults and Exceptions for Ontology Interoperability;374
19.5;15.5 Applications;376
19.5.1;15.5.1 Annotation and Retrieval of Data;376
19.5.2;15.5.2 Statistical Analysis of Experiments;377
19.5.3;15.5.3 Automatic Annotation and Community-Developed Ontologies;378
19.5.3.1;15.5.3.1 Automatic Annotation;378
19.5.3.2;15.5.3.2 Community Development;378
19.5.4;15.5.4 Reasoning for Experimental Hypothesis Testing;379
19.6;15.6 Summary and Conclusions;379
19.7;References;380
20;16 The Ontology of Medical Terminological Systems: Towards the Next Generation of Medical Ontologies;383
20.1;16.1 Introduction;383
20.2;16.2 Terminological Systems and Ontologies;384
20.3;16.3 Domains and Graduated Conceptualizations;387
20.4;16.4 Analyses of Terminological Systems;389
20.5;16.5 Medical Terminological Systems;391
20.5.1;16.5.1 ICD;391
20.5.2;16.5.2 SNOMED-CT;392
20.5.3;16.5.3 UMLS;393
20.5.4;16.5.4 LOINC;394
20.5.5;16.5.5 GALEN;395
20.5.6;16.5.6 MeSH;396
20.6;16.6 Conclusions and Future Research;398
20.7;References;399
21;17 Ontologies of Language and Language Processing;402
21.1;17.1 Introduction;402
21.2;17.2 Lexical Databases and Ontology;405
21.3;17.3 Grammatical Motivation and Linguistic Ontology;408
21.4;17.4 Discussion;414
21.5;References;415
22;18 Business Ontologies;419
22.1;18.1 Introduction;419
22.1.1;18.1.1 Domain-Level Ontologies;420
22.1.2;18.1.2 Application-Level Ontologies;422
22.2;18.2 Socio-Instrumental Pragmatism;422
22.2.1;18.2.1 Restructuring the Taxonomy;423
22.2.1.1;18.2.1.1 Actors;425
22.2.1.2;18.2.1.2 Objects;425
22.2.1.3;18.2.1.3 Actions;426
22.2.1.4;18.2.1.4 Agents;427
22.2.2;18.2.2 The Resulting Meta-model;428
22.3;18.3 Enterprise Ontology;428
22.3.1;18.3.1 World Ontology Specification Language;428
22.3.2;18.3.2 The Axioms of Enterprise Ontology;431
22.3.2.1;18.3.2.1 The Operation Axiom;431
22.3.2.2;18.3.2.2 The Transaction Axiom;432
22.3.2.3;18.3.2.3 The Composition Axiom;433
22.3.2.4;18.3.2.4 The Distinction Axiom;433
22.4;18.4 Conclusion;433
22.5;References;434
23;19 Ontologies for E-government;437
23.1;19.1 Motivation;437
23.2;19.2 State of the Art in E-Government Ontologies;439
23.3;19.3 Ontologies to Formalize a Shared Understanding of Meaning;441
23.3.1;19.3.1 Starting with Terms;443
23.3.2;19.3.2 Transforming Terms and Facts to Concepts and Properties;448
23.3.3;19.3.3 Negotiating Reuse;448
23.4;19.4 Ontologies for Modelling Semantically Enriched Processes;450
23.5;19.5 Ontologies for Modelling Business Rules;453
23.5.1;19.5.1 Business Rules Classification;453
23.5.2;19.5.2 Semi-Formal Rule Respresentation;454
23.5.3;19.5.3 Formalization;456
23.5.3.1;19.5.3.1 Property Restriction;456
23.5.3.2;19.5.3.2 Semantic Web Rule Language;457
23.6;19.6 Ontologies for Modelling Agile E-Government Processes A process is considered agile when its execution model is created flexible at runtime, based on the results of triggered rules instead of static pre-defined models. ;463
23.7;19.7 Conclusion;467
23.8;References;468
24;20 An Ontology-Driven Approach and a Context Management Framework for Ubiquitous Computing Applications;471
24.1;20.1 Introduction;471
24.2;20.2 Ontology Based Modeling of Context Aware Ubiquitous Computing Systems;472
24.3;20.3 An Ontology-Driven Meta-Model for Ubiquitous Computing Systems;475
24.3.1;20.3.1 Underlying Concepts;475
24.3.2;20.3.2 Focused Ontology;477
24.3.3;20.3.3 Core vs. Application Ontology;479
24.4;20.4 Context Management Framework;480
24.4.1;20.4.1 Context Management Process;480
24.4.2;20.4.2 Rules;481
24.4.2.1;20.4.2.1 Rules for Artifact State Assessment;482
24.4.2.2;20.4.2.2 Rules for the Local Decision-Making Process;482
24.4.2.3;20.4.2.3 Rules for the Global Decision-Making Process;482
24.4.3;20.4.3 Implementation;482
24.4.4;20.4.4 Engineering Applications;484
24.5;20.5 Prototype Application Example;485
24.5.1;20.5.1 Scenario;485
24.5.2;20.5.2 Components;486
24.5.3;20.5.3 Implementation;486
24.5.4;20.5.4 Semantic-Based Service Discovery;489
24.6;20.6 Conclusions;491
24.7;References;491
25;21 Category Theory as a Mathematics for Formalizing Ontologies;494
25.1;21.1 Introduction;494
25.2;21.2 Categories;497
25.3;21.3 Limits, Colimits, and Concepts as Theories;501
25.4;21.4 Structural Mappings;506
25.5;21.5 Categories of Categories, Functors, and Natural Transformations;509
25.6;21.6 Universal Arrows and Adjunctions;512
25.7;References;515
26;22 Issues of Logic, Algebra and Topology in Ontology;518
26.1;22.1 Introduction;518
26.2;22.2 Ingredients of Logic;520
26.2.1;22.2.1 Interpretations and Ontology;523
26.2.2;22.2.2 Theories and Models;524
26.3;22.3 Geometric Logic;525
26.3.1;22.3.1 Rules of Inference;526
26.3.2;22.3.2 Soundness;528
26.3.3;22.3.3 Beyond Rules of Inference;529
26.3.4;22.3.4 Geometric Ontology;530
26.4;22.4 Topology;533
26.5;22.5 Algebra;533
26.5.1;22.5.1 Lists and Finite Sets;534
26.5.2;22.5.2 Free Algebras;535
26.6;22.6 Categories;536
26.6.1;22.6.1 Sheaves;537
26.7;References;538
27;23 The Institutional Approach;539
27.1;23.1 Introduction;539
27.1.1;23.1.1 Ontologies;541
27.1.2;23.1.2 Semantic Integration;543
27.1.3;23.1.3 Architecture;545
27.2;23.2 Contexts;548
27.2.1;23.2.1 General Theory;548
27.2.2;23.2.2 Special Theory;551
27.3;23.3 Indexed Contexts;553
27.3.1;23.3.1 General Theory;553
27.3.2;23.3.2 Special Theory;555
27.4;23.4 Diagrams;557
27.4.1;23.4.1 General Theory;557
27.4.2;23.4.2 Special Theory;559
27.5;23.5 Coalescence;564
27.6;23.6 Fusion;564
27.6.1;23.6.1 General Theory;564
27.6.2;23.6.2 Special Theory;566
27.7;23.7 Formalism;568
27.8;References;569
28;24 Ontology Engineering, Universal Algebra, and Category Theory;570
28.1;24.1 Introduction;570
28.2;24.2 Representing Ontologies;571
28.3;24.3 Presenting Ontologies;573
28.4;24.4 Views Versus Sub-Ontologies;575
28.5;24.5 Interoperations;575
28.6;24.6 Solving View Updates;577
28.7;24.7 Interoperations with Instances;578
28.8;24.8 Nulls and Partial Functions;579
28.9;24.9 Universal Nulls;580
28.10;24.10 Conclusion;580
28.11;References;581