Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2023 May 19;6:89. doi: 10.1038/s41746-023-00830-x

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

PMC Copyright notice

Fig. 1 — The OMOP2OBO algorithm consists of three components: (1) Process input data. The algorithm takes as input a table of Observational Medical Outcomes Partnership (OMOP) concepts and a list of one or more OBO (Open Biological and Biomedical Ontology) Foundry ontologies. For both data types, the algorithm expects concept or class identifiers, source codes or database cross-references, labels, synonyms, and ancestor concepts or classes. (2) Map OMOP vocabulary concepts to OBO Foundry Ontology concepts. OMOP concepts are automatically mapped to OBO Foundry ontology concepts. The algorithm includes several different approaches (e.g., concept alignment and concept embedding), prioritizing those that result in high-confidence mappings. (3) Synthesize and output mapping results. The mapping results from the prior component are post-processed to include a mapping category and human-readable evidence. Post-processed mappings are serialized and able output to a variety of file types.