Validating RDF Data Quality Using Constraints to Direct the Development of Constraint Languages

For research institutes, data libraries, and data archives, RDF data validation according to predefined constraints is a much sought-after feature, particularly as this is taken for granted in the XML world. Based on our work in the DCMI RDF Application Profiles Task Group and in cooperation with the W3C Data Shapes Working Group, we identified and published by today 81 types of constraints that are required by various stakeholders for data applications. In this paper, in collaboration with several domain experts we formulate 115 constraints on three different vocabularies (DDI-RDF, QB, and SKOS) and classify them according to (1) the severity of an occurring violation and (2) the complexity of the constraint expression in common constraint languages. We evaluate the data quality of 15,694 data sets (4.26 billion triples) of research data for the social, behavioral, and economic sciences obtained from 33 SPARQL endpoints. Based on the results, we formulate several findings to direct the further development of constraint languages.