Help and feedback wanted: terminology service using OHDSI vocabulary

Hello, community! As my first post in the OHDSI forum, I would like to introduce a research project I’ve been working on related to OHDSI vocabularies, and any help or feedback would be greatly appreciated!

I work for the University of Leicester; however, this research is my own. I’ve been building a terminology server that offers multiple vocabularies, ontological exploration, semantic similarity search, auto-completion, and related workflow components using an efficient API. It currently supports multiple vocabularies, including ontologies like HPO and SNOMED, genetic symbols like Ensembl and HGNC, and pathways like Reactome. As a recent addition, it now supports OHDSI.

However, unlike many other ontologies, OHDSI vocabulary is actually many ontologies combined into one, where each concept and relationship receives an OHDSI ID but still keeps its own original properties. I wonder if there is an official mapping between the different concepts, relationships, etc. of various sub-vocabularies inside the OHDSI vocabulary? Is my current implementation correct or efficient, or does it have any important issues?

The software itself is open source, hosted at GitHub - Firefox2100/biomedical-terminology-service: This is a FastAPI service for using with biomedical terminologies, such as ontologies or vocabularies. · GitHub. One demo server is hosted by University of Leicester, under separate branding but running the same code, at https://similarity.cafevariome.org/. Please feel free to check out the software or the demo implementation, and any feedback or help is appreciated!

Hello @Firefox2100!

I’m not sure whether this is directly relevant, but I’ve been looking at a related issue in terminology mappings: cases where a mapping appears reasonable but does not fully preserve the original meaning or granularity.

A recent paper proposes a new measure called the “Mapping Burden Ratio” to quantify differences in granularity between terminology systems.

I thought it might be relevant here, since semantic similarity does not always imply mapping equivalence.

Hi @Firefox2100

Welcome to the Community!

OHDSI uses Athena as its primary resource for distributing vocabularies. OHDSI Standardized Vocabularies are also available elsewhere, but Athena is the central repository where we deliver the latest versions.

Have you been in contact with the Vocabulary Team already? We have a dedicated working group to discuss all things related to vocabularies. In August, the focus is on the upcoming release, but you are (obviously) welcome to join the discussion. The link to the working group is available here.

Also tagging @m-khitrun and @aostropolets.

PS: The demo link you posted leads to a webpage that does not seem to be working properly.