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Conference Papers Year : 2016

Automated Monitoring of Data Quality in Linked Data Systems

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.
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hal-01616350 , version 1 (13-10-2017)

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  • HAL Id : hal-01616350 , version 1

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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⟩
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