Faceted Visual Exploration of Semantic Data

  • Philipp Heim
  • Jürgen Ziegler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6431)


Tools for searching and interactively exploring the rapidly growing amount of semantically annotated data on the Web are still scarce and limited in their support of the users’ manifold goals and activities. In this paper we describe a method and a tool that allows humans to access and explore Semantic Web data more effectively, leveraging the specific characteristics of semantic data. The approach utilizes the concept of faceted search and combines it with a visualization that exploits the graph-based structure of linked semantic data. The facets are represented as nodes in a graph visualization and can be interactively added and removed by the users in order to produce individual search interfaces. This provides the possibility to generate interfaces with different levels of complexity that can search arbitrary domains accessible through the SPARQL query language. Even multiple and distantly connected facets can be integrated in the graph facilitating the access of information from different user-defined perspectives. This approach facilitates searching massive amounts of data with complex semantic relations, building highly complex search queries and supporting users who are not familiar with the Semantic Web.


Graph visualization faceted search query building SPARQL hierarchical facets pivot operation 


  1. 1.
    Berners-Lee, T., Fischetti, M.: Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by its Inventor. Harper, USA (1999)Google Scholar
  2. 2.
    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
  3. 3.
    Bizer, C., Heath, T., Kingsley, I., Berners-Lee, T.: Linked data on the Web. In: Proc. WWW 2008 Workshop: LDOW (2008)Google Scholar
  4. 4.
    Hearst, M., English, J., Sinha, R., Swearingen, K., Yee, P.: Finding the Flow in Web Site Search. Communications of the ACM 45(9), 42–49 (2002)CrossRefGoogle Scholar
  5. 5.
    Hausenblas, M., Halb, W., Raimond, Y., Heath, T.: What is the size of the Semantic Web? In: Proc. I-SEMANTICS 2008, pp. 9–16. JUCS (2008)Google Scholar
  6. 6.
    Schraefel, M.C., Smith, D., Owens, A., Russell, A., Harris, C., Wilson, M.: The evolving mSpace platform: Leveraging the Semantic Web on the trail of the memex. In: Proc. Hypertext 2005, pp. 174–183. ACM Press, New York (2005)Google Scholar
  7. 7.
    Longwell RDF Browser, SIMILE (2005),
  8. 8.
    Quan, D., Huynh, D., Karger, D.: Haystack: A Platform for Authoring End User Semantic Web Applications. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 738–753. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  9. 9.
    Huynh, D., Karger, D.: Parallax and companion: Set-based browsing for the Data Web (2009)Google Scholar
  10. 10.
    Kobilarov, G., Dickinson, I.: Humboldt: Exploring Linked Data. In: Proc. WWW 2008 Workshop: LDOW (2008)Google Scholar
  11. 11.
    Berners-Lee, T., Hollenbach, J., Lu, K., Presbrey, J., Prud’ommeaux, E., Schraefel, M.C.: Tabulator Redux: Browsing and writing Linked Data. In: Proc. WWW 2008 Workshop: LDOW (2008)Google Scholar
  12. 12.
    Huynh, D.: Nested Faceted Browser (2009),
  13. 13.
    Heim, P., Ziegler, J., Lohmann, S.: gFacet: A Browser for the Web of Data. In: Proc. SAMT 2008 Workshop: IMC-SSW 2008, pp. 49–58. CEUR-WS (2008)Google Scholar
  14. 14.
    Fruchterman, T., Reingold, E.: Graph drawing by force-directed placement. In: Softw. Pract. Exper. 1991, pp. 1129–1164. John Wiley & Sons, Chichester (1991)Google Scholar
  15. 15.
    Gray, J., Bosworth, A., Layman, A., Pirahesh, H.: Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. In: Proc. ICDE 1996, pp. 152–159. IEEE Press, New York (1996)Google Scholar
  16. 16.
    Kuhlthau, C.C.: Developing a model of the library search process: cognitive and affective aspects. Reference Quarterly, 232–242 (1988)Google Scholar
  17. 17.
    Marchionini, G.: Information seeking in electronic environments. Cambridge University Press, Cambridge (1997)Google Scholar
  18. 18.
    Bates, M.J.: Where should the person stop and the information search interface start? Information Processing and Management 26(5), 575–591 (1990)CrossRefGoogle Scholar
  19. 19.
    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. LNCS, vol. 6088, pp. 288–302. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Philipp Heim
    • 1
  • Jürgen Ziegler
    • 2
  1. 1.Visualization and Interactive Systems GroupUniversity of StuttgartGermany
  2. 2.Interactive Systems and Interaction DesignUniversity of Duisburg-EssenGermany

Personalised recommendations