Getting the Most out of Wikidata: Semantic Technology Usage in Wikipedia’s Knowledge Graph
Aus International Center for Computational Logic
Getting the Most out of Wikidata: Semantic Technology Usage in Wikipedia’s Knowledge Graph
Stanislav MalyshevStanislav Malyshev, Markus KrötzschMarkus Krötzsch, Larry GonzálezLarry González, Julius GonsiorJulius Gonsior, Adrian BielefeldtAdrian Bielefeldt
Stanislav Malyshev, Markus Krötzsch, Larry González, Julius Gonsior, Adrian Bielefeldt
Getting the Most out of Wikidata: Semantic Technology Usage in Wikipedia’s Knowledge Graph
In Denny Vrandečić, Kalina Bontcheva, Mari Carmen Suárez-Figueroa, Valentina Presutti, Irene Celino, Marta Sabou, Lucie-Aimée Kaffee, Elena Simperl, eds., Proceedings of the 17th International Semantic Web Conference (ISWC'18), volume 11137 of LNCS, 376-394, 2018. Springer
Getting the Most out of Wikidata: Semantic Technology Usage in Wikipedia’s Knowledge Graph
In Denny Vrandečić, Kalina Bontcheva, Mari Carmen Suárez-Figueroa, Valentina Presutti, Irene Celino, Marta Sabou, Lucie-Aimée Kaffee, Elena Simperl, eds., Proceedings of the 17th International Semantic Web Conference (ISWC'18), volume 11137 of LNCS, 376-394, 2018. Springer
- KurzfassungAbstract
Wikidata is the collaboratively curated knowledge graph of the Wikimedia Foundation (WMF), and the core project of Wikimedia’s data management strategy. A major challenge for bringing Wikidata to its full potential was to provide reliable and powerful services for data sharing and query, and the WMF has chosen to rely on semantic technologies for this purpose. A live SPARQL endpoint, regular RDF dumps, and linked data APIs are now forming the backbone of many uses of Wikidata. We describe this influential use case and its underlying infrastructure, analyse current usage, and share our lessons learned and future plans. - Bemerkung: Note: The data used in this publication is available in the form of anonymised Wikidata SPARQL query logs. There are some minor discrepancies in the counts due to small changes in the pre-processing done on the logs that were eventually published. The paper has won the Best Paper Award in the In-Use Track of ISWC 2018.
- Projekt:Project: Cfaed, DIAMOND, HAEC B08, Wikidata
- Forschungsgruppe:Research Group: Wissensbasierte SystemeKnowledge-Based Systems
@inproceedings{MKGGB2018,
author = {Stanislav Malyshev and Markus Kr{\"{o}}tzsch and Larry
Gonz{\'{a}}lez and Julius Gonsior and Adrian Bielefeldt},
title = {Getting the Most out of Wikidata: Semantic Technology Usage in
Wikipedia’s Knowledge Graph},
editor = {Denny Vrande{\v{c}}i{\'{c}} and Kalina Bontcheva and Mari Carmen
Su{\'{a}}rez-Figueroa and Valentina Presutti and Irene Celino and
Marta Sabou and Lucie-Aim{\'{e}}e Kaffee and Elena Simperl},
booktitle = {Proceedings of the 17th International Semantic Web Conference
(ISWC'18)},
series = {LNCS},
volume = {11137},
publisher = {Springer},
year = {2018},
pages = {376-394}
}