To Örebro University

oru.seÖrebro University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Bridging the Semantic Gap between Sensor Data and Ontological Knowledge
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-4001-2087
2015 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

The rapid growth of sensor data can potentially enable a better awareness of the environment for humans. In this regard, interpretation of data needs to be human-understandable. For this, data interpretation may include semantic annotations that hold the meaning of numeric data. This thesis is about bridging the gap between quantitative data and qualitative knowledge to enrich the interpretation of data. There are a number of challenges which make the automation of the interpretation process non-trivial. Challenges include the complexity of sensor data, the amount of available structured knowledge and the inherent uncertainty in data. Under the premise that high level knowledge is contained in ontologies, this thesis investigates the use of current techniques in ontological knowledge representation and reasoning to confront these challenges. Our research is divided into three phases, where the focus of the first phase is on the interpretation of data for domains which are semantically poor in terms of available structured knowledge. During the second phase, we studied publicly available ontological knowledge for the task of annotating multivariate data. Our contribution in this phase is about applying a diagnostic reasoning algorithm to available ontologies. Our studies during the last phase have been focused on the design and development of a domain-independent ontological representation model equipped with a non-monotonic reasoning approach with the purpose of annotating time-series data. Our last contribution is related to coupling the OWL-DL ontology with a non-monotonic reasoner. The experimental platforms used for validation consist of a network of sensors which include gas sensors whose generated data is complex. A secondary data set includes time series medical signals representing physiological data, as well as a number of publicly available ontologies such as NCBO Bioportal repository.

Place, publisher, year, edition, pages
Örebro: Örebro university , 2015. , p. 143
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 65
Keywords [en]
Semantic Gap, Ontology, Knowledge Representation and Reasoning, Sensor Data
National Category
Information Systems
Research subject
Informatics
Identifiers
URN: urn:nbn:se:oru:diva-45908ISBN: 978-91-7529-085-0 (print)OAI: oai:DiVA.org:oru-45908DiVA, id: diva2:856399
Public defence
2015-11-20, Teknikhuset, Hörsal T, Örebro universitet, Fakultetsgatan 1, Örebro, 10:15 (English)
Opponent
Supervisors
Available from: 2015-09-24 Created: 2015-09-24 Last updated: 2018-01-11Bibliographically approved

Open Access in DiVA

Cover(669 kB)667 downloads
File information
File name COVER02.pdfFile size 669 kBChecksum SHA-512
ea13f1f6808d8c04de4d0472cfa4c65513ce671b37028fed20d6872d825d18f66c59dc408094e4f8e94700469e0a6287a82a32aad58de0c204d28c6e3359cb46
Type fulltextMimetype application/pdf

Authority records

Alirezaie, Marjan

Search in DiVA

By author/editor
Alirezaie, Marjan
By organisation
School of Science and Technology
Information Systems

Search outside of DiVA

GoogleGoogle Scholar
Total: 0 downloads
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

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 4649 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf