Phd thesis ontology

Phd thesis ontology

Nov 22,  · Although qualitative research on large samples is theoretically conceivable, time and financial constraints force qualitative researchers to sacrifice breadth for depth. PhD Assistance experts has experience in handling Dissertation And Assignment in Medical Education techniques with assured distinction. Talk to Experts Now enabling integration across different levels of detail. The use of an ontology, translated into an active, information-system component, leads Ontology-Driven Geographic Information Systems. The results of this thesis show that a model that incorporates hierarchies and roles has the potential to integrate more information than models that do not Phd Thesis Ontology, 10 Best Resume Writing Service Legal, Algebra Math Problems, Whatly Essay Contest

Ontology | Custom PHD Thesis

PhD Thesis:. Towards Methodological Principles for Ontology Phd thesis ontology. Mustafa Jarrar. Vrije Universiteit Brussel. May 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 phd thesis ontology applications, phd thesis ontology.

Organizations are looking towards them as vital machine-processable semantics for many application areas. An ontology in general, is an agreed understanding i. semantics of a certain domain, axiomatized and represented formally as logical theory in a computer resource. By sharing an ontologyautonomous 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, phd thesis ontology, easier to build, and smoother phd thesis ontology maintain.

Firstphd thesis ontology, 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. Secondwe 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.

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, phd thesis ontology, 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. Thirdto 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 phd thesis ontology. 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. Fundamental Challenges in Ontology Engineering. Ontology Double Articulation. Ontology Modularization, phd thesis ontology. Step 1: Composing fact types. Step 2: Composing constraints. Step 3: Reasoning about the satisfiability of ORM modules. ORM Markup Language. DogmaModeler Ontology Engineering Tool. The CCFORM Case Study. Customer Complaint ontology. Conclusions and Future Work. Contribution to ORM. 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. PhD Thesis: Towards Methodological Principles for Ontology Engineering Mustafa Jarrar Vrije Universiteit Brussel May See Table phd thesis ontology Contents below Abstract The Internet and other open connectivity environments create a strong demand for the sharing of data semantics.

Table of Contents Introduction and Overview 1. Step 3: Reasoning about the satisfiability of ORM modules 4. Customer Complaint ontology 7. PhD Thesis: Towards Methodological Principles for Ontology Engineering Mustafa Jarrar Vrije Universiteit Brussel May

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This dissertation describes the development and validation of a Common Rule Ontology (CRO), expressed in the OWL-2 Web Ontology Language, and is intended to provide a computable semantic knowledge model for assessing and representing components of the information artifacts of required as part of regulated research under 45 C.F.R. § 46 Fortunately, you don’t have to discuss ontology in great depth when writing a dissertation in business studies. Several paragraphs to one page will suffice for a dissertation on Bachelor’s or Master’s level, whereas you can devote about two pages to ontology on a research at a PhD level. You can address ontology part of methodology chapter of your dissertation in the following manner: Firstly, you can 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