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Analyzing Linked Data Quality with LiQuate
Edna Ruckhaus, Oriana Baldizán, and María-Esther Vidal
Universidad Simón Bolívar, Venezuelaeruckhaus@ldc.usb.ve
obaldizan@ldc.usb.ve
mvidal@ldc.usb.ve
Abstract. In the last years, the number of datasets in the Linking Open Data (LOD) cloud and the applications that rely on links between these datasets to discover patterns or potential new associations, have exploded. However, because of data source heterogeneity, published data may suffer of redundancy, inconsistencies or may be incomplete; thus, results generated by linked data based applications may be imprecise or unreliable. We illustrate LiQuate (Linked Data Quality Assessment), a tool that combines Bayesian Networks and rule-based systems to analyze the quality of data and links in the LOD cloud.
LNCS 8186, p. 629 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2013