Our paper on “Directing the Development of Constraint Languages by Checking Constraints on RDF Data” got accepted for publication by the International Journal of Semantic Computing.
Abstract: For research institutes, data libraries, and data archives, validating RDF data 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 two international working groups on RDF validation and jointly identified requirements to formulate constraints and validate RDF data, we have published 81 types of constraints that are required by various stakeholders for data applications.
In this paper, we evaluate the usability of identified constraint types for assessing RDF data quality by (1) collecting and classifying 115 constraints on vocabularies commonly used in the social, behavioral, and economic sciences, either from the vocabularies themselves or from domain experts, and (2) validating 15,694 data sets (4.26 billion triples) of research data against these constraints. We classify each constraint according to (1) the severity of occurring violations and (2) based on which types of constraint languages are able to express its constraint type. Based on the large-scale evaluation, we formulate several findings to direct the further development of constraint languages.
Hartmann, T., Zapilko, B., Wackerow, J., & Eckert, K. (2016). Directing the Development of Constraint Languages by Checking Constraints on RDF Data. International Journal of Semantic Computing, 10(02), 1–25. http://www.worldscientific.com/worldscinet/ijsc
Author: Prof. Dr. Kai Eckert
Date: Wed, 22 Jun 2016