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Ruben Verborgh

Sustainable Linked Data Generation: The Case of DBpedia

by Wouter Maroy, Anastasia Dimou, Dimitris Kontokostas, Ben De Meester, Ruben Verborgh, Jens Lehmann, Erik Mannens, and Sebastian Hellmann

DBpedia EF, the generation framework behind one of the Linked Open Data cloud’s central interlinking hubs, has limitations with regard to quality, coverage and sustainability of the generated dataset. DBpedia can be further improved both on schema and data level. Errors and inconsistencies can be addressed by amending (i) the DBpedia EF; (ii) the DBpedia mapping rules; or (iii) Wikipedia, from which it extracts information. However, even though the DBpedia EF and mapping rules are continuously evolving and several changes were applied to both of them, there are no significant improvements on the DBpedia dataset since its limitations were identified. To address these shortcomings, we propose adapting a different semantic-driven approach that decouples, in a declarative manner, the extraction, transformation and mapping rule execution. In this paper, we discuss the new DBpedia EF, its architecture, its technical implementation, and extraction results. The extraction time remains within the same magnitude, but the resulting extraction process is more sustainable. This way, we achieve an enhanced data generation process that can be broadly adopted, and which improves DBpedia’s quality, coverage, and sustainability.

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To be published in 2017 in The Semantic Web – ISWC 2017.

Keywords: RML, DBpedia, Linked Data, rules

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IEEE
W. Maroy, A. Dimou, D. Kontokostas, B. De Meester, R. Verborgh, J. Lehmann, E. Mannens, and S. Hellmann, “Sustainable Linked Data Generation: The Case of DBpedia,” in The Semantic Web – ISWC 2017, 2017. Accepted for publication.
ACM
Wouter Maroy et al. 2017. Sustainable Linked Data Generation: The Case of DBpedia. In The Semantic Web – ISWC 2017. Accepted for publication.
LNCS
Maroy, W., Dimou, A., Kontokostas, D., De Meester, B., Verborgh, R., Lehmann, J., Mannens, E., Hellmann, S.: Sustainable Linked Data Generation: The Case of DBpedia. In: The Semantic Web – ISWC 2017 (2017). Accepted for publication.
APA
Maroy, W., Dimou, A., Kontokostas, D., De Meester, B., Verborgh, R., Lehmann, J., … Hellmann, S. (2017). Sustainable Linked Data Generation: The Case of DBpedia. In The Semantic Web – ISWC 2017. Accepted for publication.
MLA
Maroy, Wouter et al. “Sustainable Linked Data Generation: The Case of DBpedia.” The Semantic Web – ISWC 2017. 2017. Print. Accepted for publication.

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