# Ontology Development Kit: a toolkit for building, maintaining, and standardising biomedical ontologies

arXiv: https://arxiv.org/abs/2207.02056 · HTML: https://mlsanity.com/paper/2207.02056/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jul 2022.

## Built on by (most cited first, 9 of 9)

- [Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)](https://mlsanity.com/paper/2312.10904/) (2023)
- [Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities](https://mlsanity.com/paper/2309.17255/) (2023)
- [The Artificial Intelligence Ontology: LLM-assisted construction of AI concept hierarchies](https://mlsanity.com/paper/2404.03044/) (2024)
- [Ontologizing Health Systems Data at Scale: Making Translational Discovery a Reality](https://mlsanity.com/paper/2209.04732/) (2022)
- [Applying BioBERT to Extract Germline Gene-Disease Associations for Building a Knowledge Graph from the Biomedical Literature](https://mlsanity.com/paper/2309.13061/) (2023)
- [Data-driven Coreference-based Ontology Building](https://mlsanity.com/paper/2410.17051/) (2024)
- [Chemical classification program synthesis using generative artificial intelligence](https://mlsanity.com/paper/2505.18470/) (2025)
- [PREFER: An Ontology for the PREcision FERmentation Community](https://mlsanity.com/paper/2602.16755/) (2026)
- [SciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions](https://mlsanity.com/paper/2607.27955/) (2026)

## Abstract (arXiv)

Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking, and dependency management. To manage these processes, a diverse set of tools is required, from command line utilities to powerful ontology engineering environments such as ROBOT. Particularly in the biomedical domain, which has developed a set of highly diverse yet inter-dependent ontologies, standardising release practices and metadata, and establishing shared quality standards, are crucial to enable interoperability. The Ontology Development Kit (ODK) provides a set of standardised, customisable, and automatically executable workflows, and packages all required tooling in a single Docker image. In this paper, we provide an overview of how the ODK works, show how it is used in practice, and describe how we envision it driving standardisation efforts in our community.