Abstract
This paper presents a quality assessment framework for linked sensor data and discusses a role for provenance in quality assessment.
The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.
Chapter PDF
Similar content being viewed by others
References
Baillie, C., Edwards, P., Pignotti, E.: Assessing quality in the web of linked sensor data. In: 25th Conference on Artificial Intelligence (AAAI 2011), pp. 1750–1751. AAAI Press (August 2011)
Furber, C., Hepp, M.: Using semantic web resources for data quality management. In: 17th International Conference on Knowledge Engineering and Knowledge Management, pp. 211–225 (2010)
Miles, S., Groth, P., Munroe, S., Moreau, L.: Prime: A methodology for developing provenance-aware applications. ACM Transactions on Software Engineering and Methodology 20(3), 39–46 (2009)
Page, K.R., De Roure, D.C., Martinez, K., Sadler, J.D., Kit, O.Y.: Linked sensor data: Restfully serving RDF and GML. In: International Workshop on Semantic Sensor Networks 2009, vol. 522, pp. 49–63 (October 2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Baillie, C., Edwards, P., Pignotti, E. (2012). Quality Assessment, Provenance, and the Web of Linked Sensor Data. In: Groth, P., Frew, J. (eds) Provenance and Annotation of Data and Processes. IPAW 2012. Lecture Notes in Computer Science, vol 7525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34222-6_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-34222-6_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34221-9
Online ISBN: 978-3-642-34222-6
eBook Packages: Computer ScienceComputer Science (R0)