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With the development of data based applications, data quality becomes a burning issue in the context of the Web of Data. Organizations as well as researchers need suitable methods and techniques to help ensuring web data quality along the whole process, from data transformation and publication to data querying and exploitation. Among quality dimensions, completeness is recognized as difficult to evaluate, as it often relies on gold standards and/or a reference schema that are neither always available nor realistic from a practical point of view. In this paper, we propose an approach for the assessment of RDF data completeness. The proposed solution consists, first, on inferring a schema using a frequent itemset mining approach, and second, on measuring the completeness regarding the inferred schema. The paper presents both theoretical background and experimental results performed on real-world RDF datasets.
linked Data, RDF data quality, completeness, quality evaluation
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