Assessing linked data mappings using network measures

Linked Data is at its core about the setting of links between resources. Links provide enriched semantics, pointers to extra information and enable the merging of data sets. However, as the amount of Linked Data has grown, there has been the need to automate the creation of links and such automated approaches can create low-quality links or unsuitable network structures. In particular, it is difficult to know whether the links introduced improve or diminish the quality of Linked Data. In this paper, we present LINK-QA, an extensible framework that allows for the assessment of Linked Data mappings using network metrics. We test five metrics using this framework on a set of known good and bad links generated by a common mapping system, and show the behaviour of those metrics. © 2012 Springer-Verlag.