Advertisement

Using Ontologies for Official Statistics: The Istat Experience

  • Raffaella M. Aracri
  • Roberta Radini
  • Monica Scannapieco
  • Laura ToscoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10544)

Abstract

In this paper, we illustrate some experiences by the Italian National Institute of Statistics (Istat) on using ontologies for the purpose of both data integration and data dissemination. The shown data integration project is based on the Ontology Based Data Management (OBDM) paradigm, proposed for integrating multiple and heterogeneous data sources. The dissemination experience exploits the Linked Data paradigm and led to the publication of the Istat’s Linked Open Data portal.

Keywords

OBDM OBDA LOD Ontology-driven data integration Linked Data 

References

  1. 1.
    Lenzerini, M.: Ontology-based data management. In: Proceedings of the 20th International Conference on Information and Knowledge Management (CIKM 2011), pp. 5–6 (2011)Google Scholar
  2. 2.
  3. 3.
    Console, M., Lembo, D., Santarelli, V., Savo, D.F.: Graphol: ontology representation through diagrams. In: Proceedings of the 27th International Workshop on Description Logic (2014)Google Scholar
  4. 4.
  5. 5.
    Aracri, R., De Francisci, S., Pagano, A., Scannapieco, M., Tosco, L., Valentino, L.: Publishing the 15th Italian population and housing census in linked open data. In: The Proceedings of the 2nd International Workshop on Semantic Statistics (2014)Google Scholar
  6. 6.
    Ontology Web Language (OWL), 10 February 2004. http://www.w3.org/TR/owl-ref/
  7. 7.
    Data Cube Vocabulary, 25 June 2013. http://www.w3.org/TR/2013/CR-vocab-data-cube-20130625/
  8. 8.
    Simple Knowledge Organization System (SKOS), 18 August 2009. http://www.w3.org/TR/2009/REC-skos-reference-20090818/
  9. 9.
    Asset Description Metadata Schema (ADMS). https://joinup.ec.europa.eu/asset/adms/home
  10. 10.
  11. 11.
    Lodi, G., Maccioni, A., Scannapieco, M., Scanu, M., Tosco, L.: Publishing official classification in linked open data. In: The Proceedings of the 2nd International Workshop on Semantic Statistics (2014)Google Scholar
  12. 12.
    Scannapieco, M., Tosco, L., Gillman, D., Dreyer, A., Duffes, G.: An OWL ontology for the generic statistical information model (GSIM): design and implementation. In: The Proceedings of the 4th International Workshop on Semantic Statistics (2016). http://ceur-ws.org/Vol-1654/article-03.pdf
  13. 13.
    Cotton, F., Gillman, D.: Modeling the statistical process with linked metadata. In: The Proceedings of the 3rd International Workshop on Semantic Statistics (2015). http://ceur-ws.org/Vol-1551/article-06.pdf
  14. 14.
    Dreyer, A., Duffes, G., Cotton, F.: An OWL ontology for the common statistical production architecture. In: The Proceedings of the 4th International Workshop on Semantic Statistics (2016). http://ceur-ws.org/Vol-1654/article-06.pdf
  15. 15.
    IMS – Implementing ModernStats Standard Project. http://www1.unece.org/stat/platform/pages/viewpage.action?pageId=122323917
  16. 16.
  17. 17.
    Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., Rosati, R.: Linking data to ontologies. J. Data Semant. 10, 133–173 (2008)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Raffaella M. Aracri
    • 1
  • Roberta Radini
    • 1
  • Monica Scannapieco
    • 1
  • Laura Tosco
    • 1
    Email author
  1. 1.Istat - Italian National Institute of StatisticsRomeItaly

Personalised recommendations