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Quality assessment of linked datasets using probabilistic approximation

: Debattista, Jeremy; Londono, Santiago; Lange, Christoph; Auer, Sören


Gandon, F.:
The semantic web. Latest advances and new domains. 12th European Semantic Web Conference, ESWC 2015 : Portoroz, Slovenia, May 31-June 4, 2015; Proceedings
Cham: Springer International Publishing, 2015 (Lecture Notes in Computer Science 9088)
ISBN: 978-3-319-18817-1 (Print)
ISBN: 978-3-319-18818-8 (Online)
European Semantic Web Conference (ESWC) <12, 2015, Portoroz/Slovenia>
Fraunhofer IAIS ()

With the increasing application of Linked Open Data, assessing the quality of datasets by computing quality metrics becomes an issue of crucial importance. For large and evolving datasets, an exact, deterministic computation of the quality metrics is too time consuming or expensive. We employ probabilistic techniques such as Reservoir Sampling, Bloom Filters and Clustering Coefficient estimation for implementing a broad set of data quality metrics in an approximate but sufficiently accurate way. Our implementation is integrated in the comprehensive data quality assessment framework Luzzu. We evaluated its performance and accuracy on Linked Open Datasets of broad relevance.