Enhancing Dataset Quality using Keys

The Linked Data principles provide a decentral approach for publishing structured data in RDF on the Web. A consequence of this architectural choice is a high variance in the quality of the RDF datasets which constitute the Linked Data cloud. In this demo paper, we address a particular aspect of quality, i.e., the discriminability of resources. During our demo, we will present our simple three-step approach and interface, which allows data publishers to detect the resources in their dataset that are indistinguishable with respect to a given set of properties. Our approach is highly scalable as it relies on ROCKER, a novel algorithm for key discovery. Our evaluation on DBpedia suggests that even very commonly-used data sources are still in need to significant improvement to abide by the discriminability criterion.