Abstract
The number of datasets in the Linking Open Data (LOD) cloud as well as LOD-based applications have exploded in the last years. However, because of data source heterogeneity, published data may suffer of redundancy, inconsistencies, or may be incomplete; thus, results generated by LOD-based applications may be imprecise, ambiguous, or unreliable. We demonstrate the capabilities of LiQuate (Linked Data Quality Assessment), a tool that relies on Bayesian Networks to analyze the quality of data and links in the LOD cloud.
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