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PROPheT – Ontology Population and Semantic Enrichment from Linked Data Sources

  • Marina Riga
  • Panagiotis Mitzias
  • Efstratios KontopoulosEmail author
  • Ioannis Kompatsiaris
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 822)

Abstract

Ontologies are a rapidly emerging paradigm for knowledge representation, with a growing number of applications in various domains. However, populating ontologies with massive volumes of data is an extremely challenging task. The field of ontology population offers a wide array of approaches for populating ontologies in an automated or semi-automated way. Nevertheless, most of the related tools typically analyse natural language text, while sources of more structured information like Linked Open Data would arguably be more appropriate. The paper presents PROPheT, a novel software tool for ontology population and enrichment. PROPheT can populate a local ontology model with instances retrieved from diverse Linked Data sources served by SPARQL endpoints. To the best of our knowledge, no existing tool can offer PROPheT’s diverse extent of functionality.

Keywords

Ontologies Ontology population Semantic enrichment Linked Data DBpedia 

Notes

Acknowledgements

This research received funding by the European Commission Seventh Framework Programme under Grant Agreement Number FP7-601138 PERICLES.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Marina Riga
    • 1
  • Panagiotis Mitzias
    • 1
  • Efstratios Kontopoulos
    • 1
    Email author
  • Ioannis Kompatsiaris
    • 1
  1. 1.Information Technologies InstituteThessalonikiGreece

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