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PhD Thesis: Towards Methodological Principles for Ontology Engineering Vrije Universiteit Brussel May 2005 |
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(See Table of Contents below)
Abstract
The Internet and other open connectivity environments create a strong demand for the sharing of data semantics. Emerging ontologies are increasingly becoming essential for computer science applications. Organizations are looking towards them as vital machine-processable semantics for many application areas. An ontology in general, is an agreed understanding (i.e. semantics) of a certain domain, axiomatized and represented formally as logical theory in a computer resource. By sharing an ontology, autonomous and distributed applications can meaningfully communicate to exchange data and make transactions interoperate independently of their internal technologies.
The main goal of this thesis is to present methodological principles for ontology engineering to guide ontology builders towards building ontologies that are both highly reusable and usable, easier to build, and smoother to maintain.
First, we investigate three foundational challenges in ontology engineering (namely, ontology reusability, ontology application-independence, and ontology evolution). Based on these challenges, we derive six ontology-engineering requirements. Fulfilling these requirements is the goal and motivation of our methodological principles.
Second, we present two methodological principles for ontology engineering: 1) ontology double articulation, and 2) ontology modularization. The double articulation principle suggests that an ontology be built as separate domain axiomatizations and application axiomatizations. While a domain axiomatization focuses on the characterization of the intended meaning (i.e. intended models) of a vocabulary at the domain level, application axiomatizations mainly focus on the usability of this vocabulary according to certain application/usability perspectives. An application axiomatization is intended to specify the legal models (a subset of the intended models) of the application(s)’ interest. The modularization principle suggests that application axiomatizations be built in a modular manner. Axiomatizations should be developed as a set of small modules and later composed to form, and be used as, one modular axiomatization. We define a composition operator for automatic module composition. It combines all axioms introduced in the composed modules.
Third, to illustrate the implementation of our methodological principles, we develop a conceptual markup language called ORM-ML, an ontology engineering tool prototype called DogmaModeler and a customer complaint ontology that serves as a real-life case study.
This research is a contribution to the DOGMA research project, which is a research framework for modeling, engineering, and deploying ontologies. In addition, we find we have benefited enormously from our participation in several European projects. It was through the CCFORM project (discussed extensively in chapter 7) that we were able to test and debug many ideas that resulted in this thesis. The Network of Excellence KnowledgeWeb has also proved to be a fruitful brainstorming environment that has undoubtedly improved the quality of the analyses performed and the results obtained.
Table of Contents
Introduction and Overview
1.1 Scope and motivation
1.1.1 Foundational challenges in ontology engineering
1.1.2 Types of methodologies
1.2 Summary of the main goals and contributions
1.3 Thesis outline and structural overview
Fundamental Challenges in Ontology Engineering
2.1 Ontology reusability
2.1.1 Significance of ontology reusability
2.1.2 Reusability challenges
2.1.3 Conclusion
2.2 Ontology application-independence
2.2.1 Example
2.2.2 Related work
2.2.3 Ontology usability is also important
2.2.4 Conclusion
2.3 Ontology evolution
2.3.1 The complexity of change
2.3.2 Distributed evolution
2.3.3 Alternative axiomatizations
2.3.4 Conclusion
2.4 Summary
3.1 Introduction
3.1.1 Overview of the double articulation principle
3.1.2 Example
3.2 Domain Axiomatization
3.2.1 Definition (double articulation, intended models, legal models)
3.2.2 Importance of linguistic terms in ontology engineering
3.2.3 On representing domain axiomatizations
3.2.4 Summary: properties of domain axiomatization
3.3 The notion of an ontology base
3.3.1 Definition (Lexon)
3.3.2 Definition (Concept)
3.3.3 Definition (Role)
3.3.4 Definition (Mapping lexons into first order logic)
3.3.5 The notion of context
3.3.6 Gloss
3.3.7 Further formal axiomatizations (Incorporating upper level ontologies)
3.4 Application axiomatization
3.4.1 Example
3.5 Discussion
4.1 Introduction
4.1.1 A simple example
4.2 Related work
4.3 Our approach
4.3.1 Modularity criterion
4.3.2 Module composition
4.4 Formal framework
4.4.1 Definition (Module)
4.4.2 Definition (Model, Module satisfiability)
4.4.3 Definition (Composition operator)
4.4.4 Definition (Modular axiomatization)
4.5 Composition of ORM conceptual schemes
Step 1: Composing fact types.
Step 2: Composing constraints.
Step 3: Reasoning about the satisfiability of ORM modules
4.6 Discussion and conclusions
5.1 Introduction and motivation
5.1.1 Why ORM
5.2 ORM-Markup Language
5.2.1 ORM-ML metadata
5.2.2 ORM-ML Body
5.3 Discussion and conclusions
DogmaModeler Ontology Engineering Tool
6.1 Introduction, a quick overview of DogmaModeler
6.2 Modeling domain axiomatizations in the Ontology Base
6.2.1 Context Modeling
6.2.2 Concept Modeling
6.2.3 Lexon Modeling
6.3 Modeling application axiomatizations
6.3.1 Generating ORM-ML
6.3.2 Verbalization
6.4 Validation of application axiomatization
6.5 Axiomatization libraries
6.6 Composition of axiomatization modules
6.7 Other functionalities
6.7.1 Ontology-driven forms
6.7.2 Ontology Multilingualism
6.8 Discussion and conclusions
7.1 Introduction
7.2. Customer Complaint ontology
7.2.1 Customer-complaint domain axiomatization
7.2.2 Customer-complaint application axiomatization
7.3 Discussion
7.4 Multilingual lexicalization of the CContology
7.5 Conclusions
Conclusions and Future Work
8.1 Summary
8.2 Discussion and concluding remarks
Contribution to ORM
8.3 Future Research
Appendices
Appendix A: ORM Markup Language
Appendix A1 (tree view of the ORM-ML XML-Schema)
Appendix A2 (ORM-ML XML-Schema)
Appendix A3: Complete Example
Appendix B: DogmaModeler
Appendix B1: DogmaModeler Ontology Metadata
Appendix B2: XML-Schema of ORM-ML graphical style sheets
Appendix B3: ORM Verbalization Templates
Appendix C: Customer Complaint Ontology
Appendix C1: The CCglossary
Appendix C2: Lexons in the CContology
Appendix D: Thesis Glossary
Bibliography