Expressive and Scalable Query-Based Faceted Search over SPARQL Endpoints

  • Sébastien Ferré
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8797)


Linked data is increasingly available through SPARQL endpoints, but exploration and question answering by regular Web users largely remain an open challenge. Users have to choose between the expressivity of formal languages such as SPARQL, and the usability of tools based on navigation and visualization. In a previous work, we have proposed Query-based Faceted Search (QFS) as a way to reconcile the expressivity of formal languages and the usability of faceted search. In this paper, we further reconcile QFS with scalability and portability by building QFS over SPARQL endpoints. We also improve expressivity and readability. Many SPARQL features are now covered: multidimensional queries, union, negation, optional, filters, aggregations, ordering. Queries are now verbalized in English, so that no knowledge of SPARQL is ever necessary. All of this is implemented in a portable Web application, Sparklis, and has been evaluated on many endpoints and questions.


Noun Phrase Question Answering SPARQL Query Triple Pattern Semantic Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Arenas, M., Grau, B., Kharlamov, E., Marciuška, Š., Zheleznyakov, D., Jimenez-Ruiz, E.: SemFacet: Semantic faceted search over YAGO. In: World Wide Web Conf. Companion, pp. 123–126. WWW Steering Committee (2014)Google Scholar
  2. 2.
    Codd, E., Codd, S., Salley, C.: Providing OLAP (On-line Analytical Processing) to User-Analysts: An IT Mandate. Codd & Date, Inc., San Jose (1993)Google Scholar
  3. 3.
    Dowty, D.R., Wall, R.E., Peters, S.: Introduction to Montague Semantics. D. Reidel Publishing Company (1981)Google Scholar
  4. 4.
    Ferré, S.: SQUALL: a controlled natural language for querying and updating RDF graphs. In: Kuhn, T., Fuchs, N.E. (eds.) CNL 2012. LNCS, vol. 7427, pp. 11–25. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Ferré, S., Hermann, A.: Semantic search: Reconciling expressive querying and exploratory search. 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. 177–192. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Ferré, S., Hermann, A.: Reconciling faceted search and query languages for the Semantic Web. Int. J. Metadata, Semantics and Ontologies 7(1), 37–54 (2012)CrossRefGoogle Scholar
  7. 7.
    Guyonvarch, J., Ferre, S., Ducassé, M.: Scalable Query-based Faceted Search on top of SPARQL Endpoints for Guided and Expressive Semantic Search. Research report PI-2009, IRISA (2013),
  8. 8.
    Haller, H.: QuiKey – an efficient semantic command line. In: Cimiano, P., Pinto, H.S. (eds.) EKAW 2010. LNCS (LNAI), vol. 6317, pp. 473–482. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Harth, A.: VisiNav: A system for visual search and navigation on web data. J. Web Semantics 8(4), 348–354 (2010)CrossRefGoogle Scholar
  10. 10.
    He, S., Liu, S., Chen, Y., Zhou, G., Liu, K., Zhao, J.: CASIA@QALD-3: A question answering system over linked data. In: C.U., et al. (eds.) Work. Multilingual Question Answering over Linked Data, QALD-3 (2013),
  11. 11.
    Hearst, M., Elliott, A., English, J., Sinha, R., Swearingen, K., Yee, K.P.: Finding the flow in web site search. Communications of the ACM 45(9), 42–49 (2002)CrossRefGoogle Scholar
  12. 12.
    Heim, P., Ertl, T., Ziegler, J.: Facet graphs: Complex semantic querying made easy. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part I. LNCS, vol. 6088, pp. 288–302. Springer, Heidelberg (2010)Google Scholar
  13. 13.
    Hildebrand, M., van Ossenbruggen, J., Hardman, L.: /facet: A browser for heterogeneous semantic web repositories. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 272–285. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Hoefler, P., Granitzer, M., Sabol, V., Lindstaedt, S.: Linked data query wizard: A tabular interface for the semantic web. In: Cimiano, P., Fernández, M., Lopez, V., Schlobach, S., Völker, J. (eds.) ESWC 2013. LNCS, vol. 7955, pp. 173–177. Springer, Heidelberg (2013)Google Scholar
  15. 15.
    Hyvönen, E., Mäkelä, E.: Semantic autocompletion. In: Mizoguchi, R., Shi, Z.-Z., Giunchiglia, F. (eds.) ASWC 2006. LNCS, vol. 4185, pp. 739–751. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. 16.
    Kaufmann, E., Bernstein, A.: Evaluating the usability of natural language query languages and interfaces to semantic web knowledge bases. J. Web Semantics 8(4), 377–393 (2010)CrossRefGoogle Scholar
  17. 17.
    Lopez, V., Fernández, M., Motta, E., Stieler, N.: PowerAqua: Supporting users in querying and exploring the semantic web. Semantic Web 3(3), 249–265 (2012)Google Scholar
  18. 18.
    Lopez, V., Uren, V.S., Sabou, M., Motta, E.: Is question answering fit for the semantic web?: A survey. Semantic Web 2(2), 125–155 (2011)Google Scholar
  19. 19.
    Mäkelä, E., Hyvönen, E., Saarela, S.: Ontogator - a semantic view-based search engine service for web applications. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 847–860. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  20. 20.
    McCrae, J., Spohr, D., Cimiano, P.: Linking lexical resources and ontologies on the semantic web with lemon. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 245–259. Springer, Heidelberg (2011)Google Scholar
  21. 21.
    Melo, C., Mikheev, A., Le Grand, B., Aufaure, M.A.: Cubix: A visual analytics tool for conceptual and semantic data. In: Int. Conf. Data Mining Workshops, pp. 894–897. IEEE Computer Society (2012)Google Scholar
  22. 22.
    Ngomo, A.C.N., Bühmann, L., Unger, C., Lehmann, J., Gerber, D.: Sorry, I don’t speak SPARQL: translating SPARQL queries into natural language. In: WWW, pp. 977–988 (2013)Google Scholar
  23. 23.
    Oren, E., Delbru, R., Decker, S.: Extending faceted navigation to RDF data. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 559–572. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  24. 24.
    Sacco, G.M., Tzitzikas, Y. (eds.): Dynamic taxonomies and faceted search. The information retrieval series. Springer (2009)Google Scholar
  25. 25.
    Van Kleek, M., Moore, B., Karger, D., André, P., Schraefel, M.: Atomate it! end-user context-sensitive automation using heterogeneous information sources on the web. In: Int. Conf. World Wide Web, pp. 951–960. ACM (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sébastien Ferré
    • 1
  1. 1.IRISAUniversité de Rennes 1Rennes cedexFrance

Personalised recommendations