PROPheT – Ontology Population and Semantic Enrichment from Linked Data Sources

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 popu...

Full description

Saved in:
Bibliographic Details
Published inData Analytics and Management in Data Intensive Domains pp. 157 - 168
Main Authors Riga, Marina, Mitzias, Panagiotis, Kontopoulos, Efstratios, Kompatsiaris, Ioannis
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesCommunications in Computer and Information Science
Subjects
DBpedia
Linked Data
Ontologies
Ontology population
Semantic enrichment
Online AccessGet full text

Cover

More Information
Summary: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.
ISBN:9783319965529
3319965522
ISSN:1865-0929
1865-0937
DOI:10.1007/978-3-319-96553-6_12