Enhancing the accessibility of science at The Lancet with native language abstracts

Today, 98% of peer-reviewed scientific publishing is in English, which is also the official language of most scientific events and international academic journals. UNESCO, through its Recommendation on Open Science, has called on scientific institutions to foster multilingualism in the practice of science, in scientific publications, and in academic communications. At The Lancet, we recognize the need to provide more equitable and inclusive access to scientific knowledge by providing abstracts translated into relevant languages. Following a pilot, a workflow for abstract translation was devised. I present here details of our abstract translation procedure and rollout.

Authors

Publication Details

Journal
European Science Editing
Published
2024-11-04
DOI
https://doi.org/10.3897/ese.2024.e132317
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing the accessibility of science at The Lancet with native language abstracts

Chris Wortley
European Science Editing
Biomedical Text Mining and Ontologies
article

Enhancing the accessibility of science at The Lancet with native language abstracts

Chris Wortley
article en

Abstract

Today, 98% of peer-reviewed scientific publishing is in English, which is also the official language of most scientific events and international academic journals. UNESCO, through its Recommendation on Open Science, has called on scientific institutions to foster multilingualism in the practice of science, in scientific publications, and in academic communications. At The Lancet, we recognize the need to provide more equitable and inclusive access to scientific knowledge by providing abstracts translated into relevant languages. Following a pilot, a workflow for abstract translation was devised. I present here details of our abstract translation procedure and rollout.

European Science EditingVol. 50
Quality Education
Openalex Percentile: Top 82%
Biomedical Text Mining and Ontologies
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