Where is My URI?

  • Andre ValdestilhasEmail author
  • Tommaso Soru
  • Markus Nentwig
  • Edgard Marx
  • Muhammad Saleem
  • Axel-Cyrille Ngonga Ngomo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10843)


One of the Semantic Web foundations is the possibility to dereference URIs to let applications negotiate their semantic content. However, this exploitation is often infeasible as the availability of such information depends on the reliability of networks, services, and human factors. Moreover, it has been shown that around 90% of the information published as Linked Open Data is available as data dumps and more than 60% of endpoints are offline. To this end, we propose a Web service called Where is my URI?. Our service aims at indexing URIs and their use in order to let Linked Data consumers find the respective RDF data source, in case such information cannot be retrieved from the URI alone. We rank the corresponding datasets by following the rationale upon which a dataset contributes to the definition of a URI proportionally to the number of literals. We finally describe potential use-cases of applications that can immediately benefit from our simple yet useful service.


Link discovery Linked data Endpoints URI Dereferencing 



This research has been partially supported by CNPq Brazil under grants No. 201536/2014-5 and H2020 projects SLIPO (GA no. 731581) and HOBBIT (GA no. 688227) as well as the DFG project LinkingLOD (project no. NG 105/3-2), the BMWI Projects SAKE (project no. 01MD15006E) and GEISER (project no. 01MD16014E). Thanks to special help from Ivan Ermilov and Diego Moussallem.


  1. 1.
    Auer, S., Demter, J., Martin, M., Lehmann, J.: LODStats – an extensible framework for high-performance dataset analytics. In: ten Teije, A., Völker, J., Handschuh, S., Stuckenschmidt, H., d’Acquin, M., Nikolov, A., Aussenac-Gilles, N., Hernandez, N. (eds.) EKAW 2012. LNCS (LNAI), vol. 7603, pp. 353–362. Springer, Heidelberg (2012). Scholar
  2. 2.
    Beek, W., Rietveld, L., Bazoobandi, H.R., Wielemaker, J., Schlobach, S.: LOD laundromat: a uniform way of publishing other people’s dirty data. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 213–228. Springer, Cham (2014). Scholar
  3. 3.
    Charalambidis, A., Troumpoukis, A., Konstantopoulos, S.: SemaGrow: optimizing federated SPARQL queries. In: Proceedings of the 11th International Conference on Semantic Systems, SEMANTICS 2015, pp. 121–128. ACM, New York (2015)Google Scholar
  4. 4.
    Colpaert, P., Verborgh, R., Mannens, E., Van de Walle, R.: Painless URI dereferencing using the DataTank. In: Presutti, V., Blomqvist, E., Troncy, R., Sack, H., Papadakis, I., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8798, pp. 304–309. Springer, Cham (2014). Scholar
  5. 5.
    Fernández, J.D., Beek, W., Martínez-Prieto, M.A. Arias, M.: LOD-a-lot: A queryable dump of the LOD cloud (2017)Google Scholar
  6. 6.
    Görlitz, O., Staab, S.: SPLENDID: SPARQL endpoint federation exploiting VoID descriptions. In: Hartig, O., Harth, A., Sequeda, J. F. (eds.) 2nd International Workshop on Consuming Linked Data (COLD 2011) in CEUR Workshop Proceedings, vol. 782, October 2011Google Scholar
  7. 7.
    Harris, S., Gibbins, N., Payne, T.R.: SemIndex: preliminary results from semantic web indexing (2004)Google Scholar
  8. 8.
    Lehmann, J.: DL-Learner: learning concepts in description logics. J. Mach. Learn. Res. 10(Nov), 2639–2642 (2009)MathSciNetzbMATHGoogle Scholar
  9. 9.
    Nentwig, M., Soru, T., Ngonga Ngomo, A.-C., Rahm, E.: LinkLion: a link repository for the web of data. In: Presutti, V., Blomqvist, E., Troncy, R., Sack, H., Papadakis, I., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8798, pp. 439–443. Springer, Cham (2014). Scholar
  10. 10.
    Potocki, A., Saleem, M., Soru, T., Hartig, O., Voigt, M., Ngomo, A.-C.N.: Federated SPARQL query processing via CostFed (2017)Google Scholar
  11. 11.
    Saleem, M., Kamdar, M.R., Iqbal, A., Sampath, S., Deus, H.F., Ngomo, A.-C.N.: Big linked cancer data: integrating linked TCGA and PubMed. J. Web Semant. Sci. Serv. Agents World Wide Web 27–28, 34–41 (2014). Semantic Web Challenge 2013CrossRefGoogle Scholar
  12. 12.
    Saleem, M., Kamdar, M.R., Iqbal, A., Sampath, S., Deus, H.F., Ngonga, A.-C.: Fostering serendipity through big linked data. In: Semantic Web Challenge at ISWC (2013)Google Scholar
  13. 13.
    Saleem, M., Ngonga Ngomo, A.-C.: HiBISCuS: hypergraph-based source selection for SPARQL endpoint federation. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 176–191. Springer, Cham (2014). Scholar
  14. 14.
    Vandenbussche, P.-Y., Umbrich, J., Matteis, L., Hogan, A., Buil-Aranda, C.: SPARQLES: monitoring public SPARQL endpoints. Semant. Web 8(6), 1049–1065 (2017)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.AKSW GroupUniversity of LeipzigLeipzigGermany
  2. 2.Database GroupUniversity of LeipzigLeipzigGermany
  3. 3.Leipzig University of Applied SciencesLeipzigGermany
  4. 4.Data Science GroupPaderborn UniversityPaderbornGermany

Personalised recommendations