Data Profiling for Semantic Web Data

  • Huiying Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7529)


Lots of RDF data have been published in the Semantic Web. For human users it is often rather difficult to get the big picture of a large RDF data exposed by Semantic Web applications. How to understand a large and unfamiliar RDF data becomes very important when the data schema is absent or different schemas are mixed. In this paper we describe a tool which can induce the actual schema, gather corresponding statistics, and present a UML-based visualization for the RDF data sources like SPARQL endpoints and RDF dumps. Experimental results, using six data sets from the Linked Data cloud, compare our approach and ExpLOD. The evaluations show that our approach is more efficient than ExpLOD.


Semantic Web RDF Data profiling 


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  1. 1.
    Hendler, J., Shadbolt, N., Hall, W., Berners-Lee, T., Weitzner, D.: Web Science: An Interdisciplinary Approach to Understanding the Web. Communications of the ACM 51(7), 60–69 (2008)CrossRefGoogle Scholar
  2. 2.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked Data - The Story So Far. IJSWIS 5(3), 1–22 (2009)Google Scholar
  3. 3.
    Aleman-Meza, B., Hakimpour, F., Arpinar, I.B., Sheth, A.P.: SwetoDblp Ontology of Computer Science Publications. Web Semantics: Science, Services and Agents on the World Wide Web 5(3), 151–155 (2007)CrossRefGoogle Scholar
  4. 4.
    Hassanzadeh, O., Consens, M.P.: Linked Movie Data Base. In: I-SEMANTICS, pp. 194–196 (2008)Google Scholar
  5. 5.
    Ding, L., Finin, T.: Characterizing the Semantic Web on the Web. 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. 242–257. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Cyganiak, R., Stenzhorn, H., Delbru, R., Decker, S., Tummarello, G.: Semantic Sitemaps: Efficient and Flexible Access to Datasets on the Semantic Web. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 690–704. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  7. 7.
    Langegger, A., Woß, W.: RDFStats-An Extensible RDF Statistics Generator and Library. In: 20th International Workshop on Database and Expert Systems Application, pp. 79–83 (2009)Google Scholar
  8. 8.
    Hausenblas, M., Halb, W., Raimond, Y., Feigenbaum, L., Ayers, D.: SCOVO: Using Statistics on the Web of Data. In: Aroyo, L., Traverso, P., Ciravegna, F., Cimiano, P., Heath, T., Hyvönen, E., Mizoguchi, R., Oren, E., Sabou, M., Simperl, E. (eds.) ESWC 2009. LNCS, vol. 5554, pp. 708–722. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Khatchadourian, S., Consens, M.P.: ExpLOD: Summary-Based Exploration of Interlinking and RDF Usage in the Linked Open Data Cloud. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part II. LNCS, vol. 6089, pp. 272–287. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Klyne, G., Carroll, J. (eds.): Resource Description Framework (RDF): Concepts and Abstract Syntax,
  11. 11.
    Brockmans, S., Volz, R., Eberhart, A., Löffler, P.: Visual Modeling of OWL DL Ontologies Using UML. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 198–213. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  12. 12.
    Documents Associated with Ontology Definition Metamodel (ODM) Version 1.0 (2009),

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Huiying Li
    • 1
  1. 1.School of Computer Science and EngineeringSoutheast UniversityNanjingP.R. China

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