Multilingual enrichment of disease biomedical ontologies
This work addresses the problem of costly manual translation of biomedical ontologies for researchers and practitioners, though it is incremental as it builds on existing knowledge bases and translation methods.
The study tackled the challenge of translating biomedical disease ontologies by evaluating the coverage and quality of translations using open-source knowledge bases like Wikidata across multiple languages, finding that Wikidata provided translations for a significant portion of terms but with varying quality compared to commercial tools.
Translating biomedical ontologies is an important challenge, but doing it manually requires much time and money. We study the possibility to use open-source knowledge bases to translate biomedical ontologies. We focus on two aspects: coverage and quality. We look at the coverage of two biomedical ontologies focusing on diseases with respect to Wikidata for 9 European languages (Czech, Dutch, English, French, German, Italian, Polish, Portuguese and Spanish) for both ontologies, plus Arabic, Chinese and Russian for the second one. We first use direct links between Wikidata and the studied ontologies and then use second-order links by going through other intermediate ontologies. We then compare the quality of the translations obtained thanks to Wikidata with a commercial machine translation tool, here Google Cloud Translation.