SPARQL Processing over the Linked Open Data with Automatic Endpoint Detection

  • Gergö Gombos
  • Attila Kiss
Part of the Studies in Computational Intelligence book series (SCI, volume 551)


The LOD Cloud is a collection of the available datasets of the Semantic Web. The individual datasets typically store information about one specific area. These datasets can be queried using the SPARQL query language. Since the SPARQL 1.1 standard, it is possible to query several remote datasets with one query, and to combine the received data. This can be done with the SERVICE clause. SERVICE clauses generate join operations, and each join operation increases the load of the endpoint, that is why some endpoints do not allow at all to run queries using the SERVICE clause on their web interface. Some endpoints use SPARQL 1.0 and they do not know the SERVICE clause. There are endpoints which estimate the execution time of the query, and if that reaches a limit, then the endpoint refuses to execute it. Our aim is to create a system, which is able to execute queries over the LOD Cloud, without explicitly mentioning the necessary endpoints in the SERVICE clauses. Instead, the proposed system automatically recognizes the endpoints based on conditions of the query.


Semantic Web Linked Data LOD Cloud SPARQL 


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  1. 1.
    Gottron, T., Scherp, A., Krayer, B., Peters, A.: LODatio: Using a Schema-level Index to Support Users in Finding Relevant Sources of Linked Data. In: K-CAP, pp. 105–108 (2013)Google Scholar
  2. 2.
    Ermilov, I., Martin, M., Lehmann, J., Auer, S.: Linked Open Data Statistics: Collection and Exploitation. In: Klinov, P., Mouromtsev, D. (eds.) KESW 2013. CCIS, vol. 394, pp. 242–249. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  3. 3.
    Buil-Aranda, C., Hogan, A., Umbrich, J., Vandenbussche, P.-Y.: SPARQL web-querying infrastructure: Ready for action? In: Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J.X., Aroyo, L., Noy, N., Welty, C., Janowicz, K. (eds.) ISWC 2013, Part II. LNCS, vol. 8219, pp. 277–293. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  4. 4.
    Görlitz, O., Staab, S.: Federated data management and query optimization for linked open data. In: Vakali, A., Jain, L.C. (eds.) New Directions in Web Data Management 1. SCI, vol. 331, pp. 109–137. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  5. 5.
    Husain, M.F., McGlothlin, J., Khan, L., Thuraisingham, B.: Scalable Complex Query Processing Over Large Semantic Web Data Using Cloud. In: 2011 IEEE International Conference on Cloud Computing (CLOUD). IEEE (2011)Google Scholar
  6. 6.
    Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American 284(5), 28–37 (2001)CrossRefGoogle Scholar
  7. 7.
    Prud’Hommeaux, E., Seaborne, A.: SPARQL query language for RDF. W3C Recommendation 15 (2008),
  8. 8.
    Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: A nucleus for a web of open data. In: Aberer, K., Choi, K.-S., Noy, N., Allemang, D., Lee, K.-I., Nixon, L.J.B., Golbeck, J., Mika, P., Maynard, D., Mizoguchi, R., Schreiber, G., Cudré-Mauroux, P. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Hassanzadeh, O., Consens, M.P.: Linked Movie Data Base. In: Workshop on Linked Data on the Web (LDOW 2009), Madrid, Spain (2009)Google Scholar
  10. 10.
    Rakhmawati, N.A., Umbrich, J., Karnstedt, M., Hasnain, A., Hausenblas, M.: Querying over Federated SPARQL Endpoints-A State of the Art Survey. arXiv preprint arXiv:1306.1723 (2013)Google Scholar
  11. 11.
    Lynden, S., Kojima, I., Matono, A., Tanimura, Y.: ADERIS: An adaptive query processor for joining federated SPARQL endpoints. In: Meersman, R., Dillon, T., Herrero, P., Kumar, A., Reichert, M., Qing, L., Ooi, B.-C., Damiani, E., Schmidt, D.C., White, J., Hauswirth, M., Hitzler, P., Mohania, M. (eds.) OTM 2011, Part II. LNCS, vol. 7045, pp. 808–817. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    Schwarte, A., Haase, P., Hose, K., Schenkel, R., Schmidt, M.: FedX: a federation layer for distributed query processing on linked open data. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part II. LNCS, vol. 6644, pp. 481–486. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  13. 13.
    Nikolov, A., Schwarte, A., Hütter, C.: FedSearch: Efficiently Combining Structured Queries and Full-Text Search in a SPARQL Federation. In: Alani, H., et al. (eds.) ISWC 2013, Part I. LNCS, vol. 8218, pp. 427–443. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  14. 14.
    Schmidt, M., Görlitz, O., Haase, P., Ladwig, G., Schwarte, A., Tran, T.: FedBench: A benchmark suite for federated semantic data query processing. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 585–600. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  15. 15.
    Quilitz, B., Leser, U.: Querying distributed RDF data sources with SPARQL. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 524–538. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  16. 16.
    Bishop, B., Kiryakov, A., Ognyanov, D., Peikov, I., Tashev, Z.: Velkov, ”Factforge: A fast track to the web of data. Semantic Web 2(2), 157–166 (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Eötvös Loránd UniversityBudapestHungary

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