Medical Subject Headings (MeSH)
The Medical Subject Headings (MeSH) thesaurus is a worldwide, hierarchically-organized, concept-based vocabulary for biomedical terms.
MeSH includes the vocabulary that appears in MEDLINE/PubMed, the NLM catalogue and other NLM databases. It is published by the U.S. National Library of Medicine (NLM), revised annually and expanded to include new terms.
It is used, among other things, to catalogue book and media holdings, index databases and create search profiles.
MeSH is also available in a German version. To preserve the character of the thesaurus, the original English MeSH descriptors are translated one-to-one into their German equivalents, with a particular focus on the main headwords. Common German synonyms from German-speaking countries are then added to the main headwords to give German MeSH users a more authentic and localised experience.
Download terms and conditions
The copyright for the German translation of the MeSH terminology has been held by ZB MED – Information Center Life Sciences since the beginning of 2020. Use of the German MeSH terms is subject to the CC BY 4.0 license and the terms and conditions of use (in German).
The copyright for the English MeSH terms is held by the U. S. National Library of Medicine (NLM) in Bethesda, MD. Use of the English version is subject to the NLM’s terms and conditions of use.
The German MeSH at ZB MED
In spring 2020, ZB MED – the German counterpart of the National Library of Medicine (NLM) – officially took over responsibility for translating the Medical Subject Headings. Up until the end of 2018, this task had been handled by the German Institute for Medical Documentation and Information, which was incorporated into the Federal Institute for Drugs and Medical Devices (BfArM) in 2020.
To create the German translation of MeSH, ZB MED developed a translation tool and a multi-stage curation process. The first stage of the translation process is performed using the machine translation API of an external translation service (currently DeepL). This is followed by an independent, multi-stage curation process to ensure maximum quality.
