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Semantic Annotation and Publication of Linked Open Data

  • Serena Sorrentino
  • Sonia Bergamaschi
  • Elisa Fusari
  • Domenico Beneventano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7975)

Abstract

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.

Keywords

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Serena Sorrentino
    • 1
  • Sonia Bergamaschi
    • 1
  • Elisa Fusari
    • 2
  • Domenico Beneventano
    • 1
  1. 1.DIEFUniversity of Modena and Reggio EmiliaModenaItaly
  2. 2.Graduate Student at DIEFUniversity of Modena and Reggio EmiliaModenaItaly

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