  From 2012 to 2015 together with other Linked Data community members and
experts from the social, behavioral, and economic sciences (SBE), we developed
diverse vocabularies to represent SBE metadata and tabular data in RDF. The
DDI-RDF Discovery Vocabulary (DDI-RDF) is designed to support the
dissemination, management, and reuse of unit-record data, i.e., data about
individuals, households, and businesses, collected in form of responses to
studies and archived for research purposes. The RDF Data Cube Vocabulary (QB)
is a W3C recommendation for expressing data cubes, i.e. multi-dimensional
aggregate data and its metadata. Physical Data Description (PHDD) is a
vocabulary to model data in rectangular format, i.e., tabular data. The data
could either be represented in records with character-separated values (CSV) or
fixed length. The Simple Knowledge Organization System (SKOS) is a vocabulary
to build knowledge organization systems such as thesauri, classification
schemes, and taxonomies. XKOS is a SKOS extension to describe formal
statistical classifications.
  To ensure high quality of and trust in both metadata and data, their
representation in RDF must satisfy certain criteria - specified in terms of RDF
constraints. In this paper, 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. We checked 115 constraints
on three different and representative SBE vocabularies (DDI-RDF, QB, and SKOS)
by means of the RDF Validator, a validation environment which is available at
http://purl.org/net/rdfval-demo.
