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One of the big challenges in Linked Data consumption is to create visual andnatural language interfaces to the data usable for non-technical users. Ontodiaprovides support for diagrammatic data exploration, showcased in thispublication in combination with the Wikidata dataset. We present improvementsto the natural language interface regarding exploring and querying Linked Dataentities. The method uses models of distributional semantics to find and rankentity properties related to user input in Ontodia. Various word embeddingtypes and model settings are evaluated, and the results show that userexperience in visual data exploration benefits from the proposed approach.

Using Word Embeddings for Visual Data Exploration with Ontodia and Wikidata