Change search
ReferencesLink to record
Permanent link

Direct link
Leveraging Ontology Technologies for Data Modeling in Space Engineering
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Systems Engineering has been a key interdisciplinary approach for the development of complex engineering projects for quite some time, and naturally, because of the wide range of disciplines involved in space programs it has been applied in this industry. Software technologies have been assisting this approach with domain-specific modeling software. As a result, descriptive models of systems are possible (mechanic, electric, etc.). There is a variety of possibilities to produce models and to model data. A natural evolution of Systems Engineering: Model Based Systems Engineering, relies on the use of a centralized system model to support diverse engineering activities throughout the life cycle of a project. Modeling languages such as UML and Ecore are popular for developing applications and models. However, other techniques such as ontologies are used in areas other than engineering to produce models of things. In this thesis, the properties of OWL ontologies are analysed and exploited for the development of data categories which are intended to describe discipline-specific properties of a system and hence, translate into benefits for engineering tasks. In this thesis, a model of a spacecraft is proposed which makes use of different data categories and allows to assess ontology features such as reasoning and inference, disjoint axioms and multiple instantiation of classes in order to represent different system levels. Furthermore, the desired model is used in an Ecore based solution that adopted some ontology concepts in order to have a comparison to currently existing technologies. An analysis of implications, opportunities and limitations is performed for both approaches and a recommendation for the future of data modeling is derived.

Place, publisher, year, edition, pages
Keyword [en]
Keyword [sv]
URN: urn:nbn:se:ltu:diva-58918Local ID: f78a5b30-9cf6-49cc-933f-889dcd8bd751OAI: diva2:1032306
Subject / course
Student thesis, at least 30 credits
Educational program
Space Engineering, master's level
Validerat; 20131016 (global_studentproject_submitter)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

Open Access in DiVA

fulltext(3760 kB)0 downloads
File information
File name FULLTEXT02.pdfFile size 3760 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 1 hits
ReferencesLink to record
Permanent link

Direct link