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.
2nd International Workshop on Computational History and Data-Driven Humanities (CHDDH), May 2016, Dublin, Ireland. IFIP Advances in Information and Communication Technology, AICT-482, pp.121-123, 2016, Computational History and Data-Driven Humanities
https://hal.inria.fr/hal-01616350
Contributeur : Hal Ifip
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Dernière modification le : vendredi 13 octobre 2017 - 15:42:47
Document(s) archivé(s) le : dimanche 14 janvier 2018 - 14:39:10
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. IFIP Advances in Information and Communication Technology, AICT-482, pp.121-123, 2016, Computational History and Data-Driven Humanities. 〈hal-01616350〉
