LinkLion: A Link Repository for the Web of Data
Links between knowledge bases build the backbone of the Web of Data. Consequently, numerous applications have been developed to compute, evaluate and infer links. Still, the results of many of these applications remain inaccessible to the tools and frameworks that rely upon it. We address this problem by presenting LinkLion, a repository for links between knowledge bases. Our repository is designed as an open-access and open-source portal for the management and distribution of link discovery results. Users are empowered to upload links and specify how these were created. Moreover, users and applications can select and download sets of links via dumps or SPARQL queries. Currently, our portal contains 12.6 million links of 10 different types distributed across 3184 mappings that link 449 datasets. In this demo, we will present the repository as well as different means to access and extend the data it contains. The repository can be found at http://www.linklion.org.
KeywordsEnsemble Learning SPARQL Query Ontology Match Triple Store Question Answering System
- 1.Hartung, M., Groß, A., Rahm, E.: Composition methods for link discovery. In: BTW (2013)Google Scholar
- 4.Ngonga Ngomo, A.-C., Auer, S.: LIMES: a time-efficient approach for large-scale link discovery on the web of data. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, IJCAI’11, vol. 3, pp. 2312–2317. AAAI Press (2011)Google Scholar
- 5.Ngonga Ngomo, A.-C., Sherif, M.A., Lyko, K.: Unsupervised link discovery through knowledge base repair. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 380–394. Springer, Heidelberg (2014)Google Scholar
- 6.Volz, J., Bizer, C., Gaedke, M., Kobilarov, G.: Silk - a link discovery framework for the web of data. In: Bizer, C., Heath, T., Berners-Lee, T., Idehen, K. (eds.) LDOW. CEUR Workshop Proceedings, vol. 538. CEUR-WS.org (2009)Google Scholar