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Automated Monitoring of Data Quality in Linked Data Systems

Kevin Feeney 1 Rajan Verma 1 Max Brunner 1 Andre Stern 1 Odhran Gavin 1, * Declan O'Sullivan 1 Rob Brennan 1
* Corresponding author
1 KDEG - Knowledge and Data Engineering Group
School of Computer Science and Statistics [Dublin]
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.
Keywords : Linked data quality metrics Data curation Visualization Semantic web
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Distributed under a Creative Commons Attribution 4.0 International License

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  • HAL Id : hal-01616350, version 1

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IFIP | IFIP-AICT | IFIP-AICT-482 | IFIP-CHDDH | IFIP-TC | IFIP-TC12 | IFIP-WG | IFIP-WG12-7

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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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