Ranking the Web of Data Jos´ e M. Gim´ enez-Garc´ ıa, Harsh Thakkar, Antoine Zimmermann 1 Univ Lyon, UJM-Saint-Etienne, CNRS, Laboratoire Hubert Curien UMR 5516, F-42023 Saint Etienne, France jose.gimenez.garcia@univ-st-etienne.fr 2 Enterprise Information Systems Lab, University of Bonn, Germany hthakkar@uni-bonn.de 3 ´ Ecole Nationale Sup´ erieure des Mines, FAYOL-ENSMSE, Laboratoire Hubert Curien, F-42023 Saint- ´ Etienne, France antoine.zimmermann@emse.fr Abstract. While a number of quality metrics have been successfully proposed for datasets in the Web of Data, there is a lack of trust metrics that can be computed for any given dataset. We argue that reuse of data can be seen as an act of trust. In the Semantic Web environment, datasets regularly include terms from other sources, and each of these connections express a degree of trust on that source. However, determining what is a dataset in this context is not straightforward. We use the concept of Pay- Level Domain to differentiate datasets, and consider usage of external terms as connections among them. Using these connections we compute the PageRank value for each dataset. This process has been performed for more than 300 datasets, extracted from the LOD Laundromat. Keywords: linked data, trust, reuse, interlinking, PageRank, quality metric, quality assessment 1 Introduction The WDAqua project 4 aims to advance the state of the art in data-driven ques- tion answering, with a special focus in the Web of Data. The Web of Data comprises thousands of datasets about varied topics, interrelated among them, which contain large quantities of relevant data to answer a question. Nonetheless, in an environment of information published independently by many different ac- tors, data veracity is usually uncertain, and there is always the risk of consuming misleading data. While some quality metrics have been proposed that can help to identify good datasets [1], there is a lack of trust metrics to provide a confidence on the veracity of the data. In this context, we argue that actual usage of data can be seen as an act of trust. In this paper we focus on reuse of resources by other datasets as an usage metric. We consider reuse of a resource of a dataset by any other given 4 http://wdaqua.informatik.uni-bonn.de