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Diagnosing Incompleteness in Wikidata with The Missing Path

Marie Destandau 1 Jean-Daniel Fekete 1
1 AVIZ - Analysis and Visualization
Inria Saclay - Ile de France, LRI - Laboratoire de Recherche en Informatique
Abstract : To make their data usable, Linked Data producers need to providea minimum level of completeness. But the task of finding the miss-ing attributes for a specific list of entities is notoriously difficult.We make the hypothesis that identifying subsets of entities witha similar structure can help finding the cause of incompletenessand decide if and how it could to be solved. We contribute with our visualisation tool: “The Missing Path”, relying on dimensional re-duction techniques to create a map of the entities based on missingproperties, revealing clusters. Users can alternate their focus withthe second coordinated visualisation that shows the distributionof properties, and of their values, datatypes and languages. We de-scribe the evaluation and iterative design process we have plannedwith Wikidata contributors.
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Submitted on : Sunday, August 2, 2020 - 10:16:50 PM
Last modification on : Tuesday, September 15, 2020 - 9:12:36 AM

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  • HAL Id : hal-02910712, version 1

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Marie Destandau, Jean-Daniel Fekete. Diagnosing Incompleteness in Wikidata with The Missing Path. Wiki Workshop 2020, Apr 2020, Taipei, Taiwan. ⟨hal-02910712⟩

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