The Ontology Lookup Service (OLS) is a repository for biomedical ontologies that aims to provide a single point of access to the latest ontology versions. It provides a website, REST API, and MCP server.

See also:

• The public OLS instance at EMBL-EBI: https://www.ebi.ac.uk/ols4/
• OLS4: a new Ontology Lookup Service for a growing interdisciplinary knowledge ecosystem
• REST API docs
• MCP endpoint (Streamable HTTP): https://www.ebi.ac.uk/ols4/api/mcp

If you use OLS in your work, please cite our recent publication in Bioinformatics.

This repository contains three projects:

• The dataloader (dataload directory)
• The API server (backend directory)
• The React frontend (frontend directory)

Deploying OLS4

First run the OLS dataload (requires Docker):

OLS4_CONFIG=./dataload/configs/efo.json ./dataload.sh

This will create Solr and Neo4j databases in the out directory. Now start the OLS stack:

HOST_UID=$(id -u) HOST_GID=$(id -g) docker compose up

You should now be able to access the OLS4 frontend at http://localhost:8081.

If you want to test it with your own ontology, copy the OWL or RDFS ontology file into this repository folder. Then make a new config file for your ontology; you can use efo.json from dataload/configs as a template. For the ontology_purl property in the config, use the relative path in this repository to your ontology e.g. ./myontology.owl. Then follow the above steps for efo with the config filename you created.

Deployment: Using Kubernetes with GitHub Packages

To deploy OLS4 using Kubernetes, Docker images built and uploaded to this repository (using GitHub Packages) are utilized. Software requirements are as follows:

1. Kubernetes command-line tool, kubectl
2. Kubernetes package manager, helm

Create data archives for Solr and Neo4j

First run the OLS dataload (requires Docker):

OLS4_CONFIG=./dataload/configs/efo.json ./dataload.sh

This will create Solr and Neo4j databases in the out directory.

Startup OLS4 deployment

Uninstall existing ols4 deployments, if any, before installing a new one. Do not forget to set KUBECONFIG environment variable.

IMPORTANT: The use of imageTag is to specify the Docker image (uploaded to this repository) that will be used in the deployment. If not familiar, simply use either the dev or stable image.

export KUBECONFIG=<K8S_CONFIG>
helm install ols4 <OLS4_DIR>/k8chart/ols4 --set imageTag=dev

Developing OLS4

OLS is different to most webapps in that its API provides both full text search and recursive graph queries, neither of which are possible and/or performant using traditional RDBMS. It therefore uses two specialized database servers: Solr, a Lucene server similar to ElasticSearch; and Neo4j, a graph database which is also used to store embedding vectors.

• The dataload directory contains the code which turns ontologies from RDF (specified using OWL and/or RDFS) into JSON and CSV datasets which can be loaded into Solr and Neo4j, respectively; and some minimal bash scripts which help with loading them.
• The backend directory contains a Spring Boot application which hosts the OLS API over the above Solr and Neo4j instances
• The frontend directory contains the React frontend built upon the backend above.

Running OLS4 components using Docker

You can run OLS4, or any combination of i

... View full README on GitHub