Assessing the Quality of Semantic Sensor Data

Chris Baillie, Peter Edwards, Edoardo Pignotti, David Corsar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Sensors are increasingly publishing observations to the Web of Linked Data. However, assessing the quality of such data remains a major challenge for agents (human and machine). This paper describes how Qual-O, a vocabulary for describing quality assessment, can be used to perform quality assessment on semantic sensor data.
Original languageEnglish
Title of host publicationProceedings of the Sixth International Workshop on Semantic Sensor Networks
EditorsOscar Corcho, Cory Henson, Payam Barnaghi
Place of PublicationAachen
PublisherCEUR-WS
Pages71-76
Number of pages6
Volume1063
Publication statusPublished - 14 Oct 2013
Event6th International Workshop on Semantic Sensor Networks - Sydney, Australia
Duration: 21 Oct 201322 Oct 2013

Publication series

NameCEUR Workshop Proceedings
ISSN (Electronic)1613-0073

Workshop

Workshop6th International Workshop on Semantic Sensor Networks
CountryAustralia
CitySydney
Period21/10/1322/10/13

Keywords

  • Semantic Web
  • Linked Data
  • ontology
  • quality
  • provenance

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  • Cite this

    Baillie, C., Edwards, P., Pignotti, E., & Corsar, D. (2013). Assessing the Quality of Semantic Sensor Data. In O. Corcho, C. Henson, & P. Barnaghi (Eds.), Proceedings of the Sixth International Workshop on Semantic Sensor Networks (Vol. 1063, pp. 71-76). (CEUR Workshop Proceedings). CEUR-WS. http://ceur-ws.org/Vol-1063/