DBpedia is a large-scale, cross-domain knowledge graph extracted from Wikipedia. For the extraction, crowd-sourced mappings from Wikipedia infoboxes to the DBpedia ontology are utilized. In this process, different problems may arise: users may create wrong and/or inconsistent mappings, use the ontology in an unforeseen way, or change the ontology without considering all possible consequences. In this paper, we present a data-driven approach to discover problems in mappings as well as in the ontology and its usage in a joint, data-driven process. We show both quantitative and qualitative results about the problems identified, and derive proposals for altering mappings and refactoring the DBpedia ontology.
CITATION STYLE
Paulheim, H. (2017). Data-driven joint debugging of the DBpedia mappings and ontology: Towards addressing the causes instead of the symptoms of data quality in DBpedia. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10249 LNCS, pp. 404–418). Springer Verlag. https://doi.org/10.1007/978-3-319-58068-5_25
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