Introduction Over the last years, several tools have been developed with the aim of efficiently supporting the link discovery process [5,7]. This process consisting of two steps: (1) Discovering a Link Specifications (LS) for retrieving high-quality links (i.e. achieve high precision and recall). (2) Carry out the LS to compute the actual links. Several frameworks such as LIMES [3] and SILK [1] have been developed to create such links between the different knowledge bases (KB). While the importance of links between datasets is unequivocal, only few efforts have aimed at making LS available. Such a link repository would however enable a large number of applications, including transfer learning for LS, the provision of provenance and justification information for links, fuzzy inferences on Linked data sets and many more. The importance of links is further underlined by the community efforts have already led to the creation of link repositories such as LinkLion and sameAs.org. In view of the dispersed availability of LS in different formats (scripts, XML, RDF), we created Lion’s Den as a companion project to LinkLion. LinkLion is a store for the publication, retrieval and use of links between KB. The portal provides functionality for the upload and the storage of discovered links, as well as meta-information about these links. With Lion’s Den, we introduce an extension of such meta-information by letting the portal user upload files describing LS. We published the Lion’s Den dataset on the LinkLion link discovery portal so as to make them accessible and queryable via a SPARQL endpoint.1.
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