Skip to main content

Extraction and Visualization of TBox Information from SPARQL Endpoints

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10024)

Abstract

The growing amount of data being published as Linked Data has a huge potential, but the usage of this data is still cumbersome, especially for non-technical users. Visualizations can help to get a better idea of the type and structure of the data available in some SPARQL endpoint, and can provide a useful starting point for querying and analysis. We present an approach for the extraction and visualization of TBox information from Linked Data. SPARQL queries are used to infer concept information from the ABox of a given endpoint, which is then gradually added to an interactive VOWL graph visualization. We implemented the approach in a web application, which was tested on several SPARQL endpoints and evaluated in a qualitative user study with promising results.

Keywords

  • Linked data
  • Concept extraction
  • Visualization
  • Ontology
  • SPARQL
  • RDF
  • OWL
  • TBox

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-49004-5_46
  • Chapter length: 16 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-49004-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.

Notes

  1. 1.

    A live demo of LD-VOWL is available at: http://ldvowl.visualdataweb.org.

  2. 2.

    The complete list of questions is available at http://ldvowl.visualdataweb.org.

  3. 3.

    http://data.nobelprize.org/sparql.

  4. 4.

    http://vocabulary.semantic-web.at/PoolParty/sparql/AustrianSkiTeam.

  5. 5.

    http://data.nobelprize.org/terms.

  6. 6.

    http://dbpedia.org/ontology.

  7. 7.

    http://dbpedia.org/class.

  8. 8.

    SPARQL Endpoints Status: http://sparqles.okfn.org.

References

  1. Bostock, M., Ogievetsky, V., Heer, J.: \(\text{ D }^3\) data-driven documents. IEEE Trans. Vis. Comput. Graph. 17(12), 2301–2309 (2011)

    CrossRef  Google Scholar 

  2. Camarda, D.V., Mazzini, S., Antonuccio, A.: LodLive, exploring the web of data. In: 8th International Conference on Semantic Systems (I-SEMANTICS 2012), pp. 197–200. ACM (2012)

    Google Scholar 

  3. Cortis, K.: ACE: a concept extraction approach using linked open data. In: Concept Extraction Challenge at the Workshop on ‘Making Sense of Microposts’. In: CEUR Workshop Proceedings, vol. 1019, pp. 31–35. CEUR-WS.org (2013)

    Google Scholar 

  4. Damljanovic, D., Stankovic, M., Laublet, P.: Linked data-based concept recommendation: comparison of different methods in open innovation scenario. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 24–38. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  5. Haag, F., Lohmann, S., Siek, S., Ertl, T.: QueryVOWL: a visual query notation for linked data. In: Gandon, F., Guéret, C., Villata, S., Breslin, J., Faron-Zucker, C., Zimmermann, A. (eds.) ESWC 2015. LNCS, vol. 9341, pp. 387–402. Springer, Heidelberg (2015). doi:10.1007/978-3-319-25639-9_51

    CrossRef  Google Scholar 

  6. Hasan, R., Gandon, F.L.: A machine learning approach to SPARQL query performance prediction. In: WI-IAT (2), pp. 266–273. IEEE Computer Society (2014)

    Google Scholar 

  7. Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on the Semantic Web. Morgan & Claypool Publishers, San Rafael (2011)

    Google Scholar 

  8. Heim, P., Hellmann, S., Lehmann, J., Lohmann, S., Stegemann, T.: RelFinder: revealing relationships in RDF knowledge bases. In: Chua, T.-S., Kompatsiaris, Y., Mérialdo, B., Haas, W., Thallinger, G., Bailer, W. (eds.) SAMT 2009. LNCS, vol. 5887, pp. 182–187. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

  9. Kirchberg, M., Leonardi, E., Tan, Y.S., Link, S., Ko, R.K.L., Lee, B.S.: Formal concept discovery in semantic web data. In: Domenach, F., Ignatov, D.I., Poelmans, J. (eds.) ICFCA 2012. LNCS, vol. 7278, pp. 164–179. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  10. Lohmann, S., Link, V., Marbach, E., Negru, S.: WebVOWL: web-based visualization of ontologies. In: Lambrix, P., Hyvönen, E., Blomqvist, E., Presutti, V., Qi, G., Sattler, U., Ding, Y., Ghidini, C. (eds.) EKWA 2014 Satellite Events. LNCS, vol. 8982, pp. 154–158. Springer, Heidelberg (2015)

    Google Scholar 

  11. Lohmann, S., Negru, S., Haag, F., Ertl, T.: Visualizing ontologies with VOWL. Semant. Web 7(4), 399–419 (2016)

    CrossRef  Google Scholar 

  12. Negru, S., Lohmann, S., Haag, F.: VOWL: visual notation for OWL ontologies (2014). http://purl.org/vowl/

  13. Peroni, S., Motta, E., d’Aquin, M.: Identifying key concepts in an ontology, through the integration of cognitive principles with statistical and topological measures. In: Domingue, J., Anutariya, C. (eds.) ASWC 2008. LNCS, vol. 5367, pp. 242–256. Springer, Heidelberg (2008)

    CrossRef  Google Scholar 

  14. Presutti, V., Aroyo, L., Adamou, A., Schopman, B.A.C., Gangemi, A., Schreiber, G.: Extracting core knowledge from linked data. In: 2nd International Workshop on Consuming Linked Data (COLD 2011), CEUR Workshop Proceedings, vol. 782. CEUR-WS.org (2011)

    Google Scholar 

  15. Shneiderman, B.: The eyes have it: a task by data type taxonomy for information visualizations. In: 1996 IEEE Symposium on Visual Languages (VL 1996), pp. 336–343. IEEE (1996)

    Google Scholar 

  16. Stankovic, M., Breitfuss, W., Laublet, P.: Linked-data based suggestion of relevant topics. In: 7th International Conference on Semantic Systems (I-SEMANTICS 2011), pp. 49–55. ACM (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Steffen Lohmann .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Weise, M., Lohmann, S., Haag, F. (2016). Extraction and Visualization of TBox Information from SPARQL Endpoints. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10024. Springer, Cham. https://doi.org/10.1007/978-3-319-49004-5_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49004-5_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49003-8

  • Online ISBN: 978-3-319-49004-5

  • eBook Packages: Computer ScienceComputer Science (R0)