Abstract : This paper describes the Dacura system’s ability to monitor data quality. This is evaluated in an experiment where a dataset of historical political
violence is collected, enriched, interlinked, and published. The results of the experiment demonstrate that automated quality measures enable the construction of publication pipelines which allow datasets to evolve rapidly without loss of quality.
https://hal.inria.fr/hal-01616350 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Friday, October 13, 2017 - 3:21:20 PM Last modification on : Friday, October 13, 2017 - 3:42:47 PM Long-term archiving on: : Sunday, January 14, 2018 - 2:39:10 PM
Kevin Feeney, Rajan Verma, Max Brunner, Andre Stern, Odhran Gavin, et al.. Automated Monitoring of Data Quality in Linked Data Systems. 2nd International Workshop on Computational History and Data-Driven Humanities (CHDDH), May 2016, Dublin, Ireland. pp.121-123. ⟨hal-01616350⟩