Ontology Translation: A Case Study on Translating the Gene Ontology from English to German

Abstract

For many researchers, the purpose of ontologies is sharing data. This sharing is facilitated when ontologies are available in multiple languages, but inhibited when an ontology is only available in a single language. Ontologies should be accessible to people in multiple languages, since multilingualism is inevitable in any scientific work. Due to resource scarcity, most ontologies of the biomedical domain are available only in English at present. We present techniques to translate Gene Ontology terms from English to German using DBPedia, the Google Translate API for isolated terms, and the Google Translate API for terms in sentential context. Average fluency scores for the three methods were 4.0, 4.4, and 4.5, respectively. Average adequacy scores were 4.0, 4.9, and 4.9.

Multilingual enrichment of disease biomedical ontologies

“…The results of this work may not be generalized to all types of entities. Hailu et al (2014) have found equivalent results for the translation of the Gene Ontology between English and German, but Silva et al (2015) did not find the same results on their partial translation of MeSH.…”

“…We also go further than these firstorder links and explore the possibility of using secondorder links to improve the coverage of the mappings between the sources. Compared to the same works, we also present a more complete study, Hailu et al (2014) only evaluate on 75 terms and Silva et al (2015) on 191 terms. We compare the coverage and quality of the entire biomedical ontology containing 10,444 terms.…”

“…Then, a human-inthe-loop validates the newly found entities, adding them to the dictionary if they are correct, or down-voting the context if they are not relevant entities. Hailu et al (2014) work on the translation of the Gene Ontology from English to German and compare three different approaches: DBpedia, the Google Translate API without context, and the Google Translate API with context. To find the terms in DBpedia they use keyword-based search.…”

“…We elaborate on these ideas by adding some elements. First of all, compared to Hailu et al (2014) and Silva et al (2015), we use already existing properties to perform the matching between the biomedical ontology and the knowl-edge graph, which should improve the quality with regard to the previous works. We also go further than these firstorder links and explore the possibility of using secondorder links to improve the coverage of the mappings between the sources.…”

Towards Multi-Lingual Pneumonia Research Data Collection Using the Community-Acquired Pneumonia International Cohort Study Database

“…A recent study suggests automated translation services, like Google Translate, may begin to be efficient tools for medical translation, as they were able to extract consistent translations and data from Latin-based language manuscripts [13]. Google Translate was also used to provide an effective translation of the Gene Ontology from English to German [14]. The Global Public Health Intelligence Network (GPHIN) was designed to process data from news sources across the globe and uses automated translation across nine languages to provide aggregate information regarding disease outbreaks [15].…”