Semantic Annotation and Publication of Linked Open Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7975)


Nowadays, there has been an increment of open data government initiatives promoting the idea that particular data produced by public administrations (such as public spending, health care, education etc.) should be freely published. However, the great majority of these resources is published in an unstructured format (such as spreadsheets or CSV) and is typically accessed only by closed communities. Starting from these considerations, we propose a semi-automatic experimental methodology for facilitating resource providers in publishing public data into the Linked Open Data (LOD) cloud, and for helping consumers (companies and citizens) in efficiently accessing and querying them. We present a preliminary method for publishing, linking and semantically enriching open data by performing automatic semantic annotation of schema elements. The methodology has been applied on a set of data provided by the Research Project on Youth Precariousness, of the Modena municipality, Italy.


Semantic Annotation Schema Element Word Sense Disambiguation SPARQL Query Link Open Data 
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.
    Beneventano, D.: Provenance based conflict handling strategies. In: Yu, H., Yu, G., Hsu, W., Moon, Y.-S., Unland, R., Yoo, J. (eds.) DASFAA Workshops 2012. LNCS, vol. 7240, pp. 286–297. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  2. 2.
    Bergamaschi, S., Castano, S., Vincini, M.: Semantic integration of semistructured and structured data sources. SIGMOD Record 28(1), 54–59 (1999)CrossRefGoogle Scholar
  3. 3.
    Bergamaschi, S., Po, L., Sala, A., Sorrentino, S.: Data source annotation in data integration systems. In: Fifth International Workshop on Databases, Information Systems and Peer-to-Peer Computing, DBISP2P (2007)Google Scholar
  4. 4.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Semantic Web Inf. Syst. 5(3), 1–22 (2009)CrossRefGoogle Scholar
  5. 5.
    Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: Dbpedia - a crystallization point for the web of data. J. Web Sem. 7(3), 154–165 (2009)CrossRefGoogle Scholar
  6. 6.
    Coletta, R., Castanier, E., Valduriez, P., Frisch, C., Ngo, D., Bellahsene, Z.: Public data integration with websmatch. CoRR, abs/1205.2555 (2012)Google Scholar
  7. 7.
    Cruz, I.F., Palmonari, M., Caimi, F., Stroe, C.: Towards “on the go” matching of linked open data ontologies. In: LDH, pp. 37–42 (2011)Google Scholar
  8. 8.
    Duchateau, F., Coletta, R., Bellahsene, Z., Miller, R.J. (not) yet another matcher. In: Cheung, D.W.-L., Song, I.-Y., Chu, W.W., Hu, X., Lin, J.J. (eds.) CIKM, pp. 1537–1540. ACM (2009)Google Scholar
  9. 9.
    Euzenat, J., Shvaiko, P.: Ontology matching. Springer, Heidelberg, DE (2007)zbMATHGoogle Scholar
  10. 10.
    Fusari, E.: Linked open data: pubblicazione, arricchimento semantico e linking di dataset pubblici attraverso il sistema momis. Master Degree Thesis (2012),
  11. 11.
    Gliozzo, A.M., Strapparava, C., Dagan, I.: Unsupervised and supervised exploitation of semantic domains in lexical disambiguation. Computer Speech & Language 18(3), 275–299 (2004)CrossRefGoogle Scholar
  12. 12.
    Heise, A., Naumann, F.: Integrating open government data with stratosphere for more transparency. J. Web Sem. 14, 45–56 (2012)CrossRefGoogle Scholar
  13. 13.
    Jain, P., Hitzler, P., Sheth, A.P., Verma, K., Yeh, P.Z.: Ontology alignment for linked open data. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 402–417. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  14. 14.
    Jentzsch, A., Isele, R., Bizer, C.: Silk - generating rdf links while publishing or consuming linked data. In: ISWC Posters&Demos (2010)Google Scholar
  15. 15.
    Miller, A.: Wordnet: A lexical database for english. Communications of the ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  16. 16.
    Navigli, R.: Word sense disambiguation: A survey. ACM Comput. Surv. 41(2) (2009)Google Scholar
  17. 17.
    Nešić, S., Rizzoli, A.E., Athanasiadis, I.N.: Publishing and linking semantically annotated agro-environmental resources to LOD with aGROPub. In: García-Barriocanal, E., Cebeci, Z., Okur, M.C., Öztürk, A. (eds.) MTSR 2011. CCIS, vol. 240, pp. 478–488. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  18. 18.
    Po, L., Sorrentino, S.: Automatic generation of probabilistic relationships for improving schema matching. Inf. Syst. 36(2), 192–208 (2011)CrossRefGoogle Scholar
  19. 19.
    shan Chen, P.P.: The entity-relationship model: Toward a unified view of data. ACM Transactions on Database Systems 1, 9–36 (1976)CrossRefGoogle Scholar
  20. 20.
    Sorrentino, S., Bergamaschi, S., Gawinecki, M.: Norms: An automatic tool to perform schema label normalization. In: ICDE, pp. 1344–1347 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.DIEFUniversity of Modena and Reggio EmiliaModenaItaly
  2. 2.Graduate Student at DIEFUniversity of Modena and Reggio EmiliaModenaItaly

Personalised recommendations