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Ruben Verborgh

Sustainable Linked Data Generation: The Case of DBpedia

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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Published in 2017 in Proceedings of the 16th International Semantic Web Conference.

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Cite this article easily using its BibTeX entry:

@inproceedings{maroy_iswc_2017,
  author = {Maroy, Wouter and Dimou, Anastasia and Kontokostas, Dimitris and De Meester, Ben and Verborgh, Ruben and Lehmann, Jens and Mannens, Erik and Hellmann, Sebastian},
  title = {Sustainable {Linked Data} Generation: The Case of {DBpedia}},
  booktitle = {Proceedings of the 16th International Semantic Web Conference},
  editor = {d'Amato, Claudia and Fernandez, Miriam and Tamma, Valentina and Lecue, Freddy and Cudr\'e-Mauroux, Philippe and Sequeda, Juan and Lange, Christoph and Heflin, Jeff},
  year = 2017,
  month = oct,
  pages = {297--313},
  publisher = {Springer},
  isbn = {978-3-319-68204-4},
  doi = {10.1007/978-3-319-68204-4_28},
  url = {http://jens-lehmann.org/files/2017/iswc_dbpedia_rml.pdf},
}

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ACM
Wouter Maroy, Anastasia Dimou, Dimitris Kontokostas, Ben De Meester, Ruben Verborgh, Jens Lehmann, Erik Mannens, and Sebastian Hellmann. 2017. Sustainable Linked Data Generation: The Case of DBpedia. In Proceedings of the 16th International Semantic Web Conference, Springer, 297–313.
APA
Maroy, W., Dimou, A., Kontokostas, D., De Meester, B., Verborgh, R., Lehmann, J., Mannens, E., & Hellmann, S. (2017). Sustainable Linked Data Generation: The Case of DBpedia. In C. d’Amato, M. Fernandez, V. Tamma, F. Lecue, P. Cudré-Mauroux, J. Sequeda, C. Lange, & J. Heflin (Eds.), Proceedings of the 16th International Semantic Web Conference (pp. 297–313). Springer.
IEEE
W. Maroy et al., “Sustainable Linked Data Generation: The Case of DBpedia,” in Proceedings of the 16th International Semantic Web Conference, 2017, pp. 297–313.
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: d’Amato, C., Fernandez, M., Tamma, V., Lecue, F., Cudré-Mauroux, P., Sequeda, J., Lange, C., and Heflin, J. (eds.) Proceedings of the 16th International Semantic Web Conference. pp. 297–313. Springer (2017).
MLA
Maroy, Wouter, et al. “Sustainable Linked Data Generation: The Case of DBpedia.” Proceedings of the 16th International Semantic Web Conference, edited by Claudia d’Amato et al., Springer, 2017, pp. 297–313.

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