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From 2012 to 2015 together with other Linked Data community members andexperts from the social, behavioral, and economic sciences (SBE), we developeddiverse vocabularies to represent SBE metadata and tabular data in RDF. TheDDI-RDF Discovery Vocabulary (DDI-RDF) is designed to support thedissemination, management, and reuse of unit-record data, i.e., data aboutindividuals, households, and businesses, collected in form of responses tostudies and archived for research purposes. The RDF Data Cube Vocabulary (QB)is a W3C recommendation for expressing data cubes, i.e. multi-dimensionalaggregate data and its metadata. Physical Data Description (PHDD) is avocabulary to model data in rectangular format, i.e., tabular data. The datacould either be represented in records with character-separated values (CSV) orfixed length. The Simple Knowledge Organization System (SKOS) is a vocabularyto build knowledge organization systems such as thesauri, classificationschemes, and taxonomies. XKOS is a SKOS extension to describe formalstatistical classifications.  To ensure high quality of and trust in both metadata and data, theirrepresentation in RDF must satisfy certain criteria - specified in terms of RDFconstraints. In this paper, we evaluate the data quality of 15,694 data sets(4.26 billion triples) of research data for the social, behavioral, andeconomic sciences obtained from 33 SPARQL endpoints. We checked 115 constraintson three different and representative SBE vocabularies (DDI-RDF, QB, and SKOS)by means of the RDF Validator, a validation environment which is available athttp://purl.org/net/rdfval-demo.

Evaluating the Quality of RDF Data Sets on Common Vocabularies in the Social, Behavioral, and Economic Sciences