Assessing Quality in the Web of Linked Sensor Data

Christopher Colin Baillie, Pete Edwards, Edoardo Pignotti

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)


Assessing the quality of sensor data available on the Web is essential in order to identify reliable information for decision-making. This paper discusses how prove- nance of sensor observations and previous quality rat- ings can influence quality assessment decisions.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence
EditorsWolfram Burgard, Dan Roth
Place of PublicationMenlo Park, California
PublisherAAAI Press
Number of pages2
ISBN (Electronic)978-1-57735-511-3
ISBN (Print)978-1-57735-507-6
Publication statusPublished - 7 Aug 2011


  • linked data
  • sensor
  • information quality
  • provenance


Dive into the research topics of 'Assessing Quality in the Web of Linked Sensor Data'. Together they form a unique fingerprint.

Cite this