Hi @Merel et al. from the Kedro team. We recently published a new repository of an open-source data resource for biomedical science constructed using Kedro. This work was done at Harvard University. Here is the released links for OptimusKG: • Website: optimuskg.ai, • Repository: https://github.com/mims-harvard/OptimusKG • Paper: https://arxiv.org/pdf/2604.27269 • Client: https://pypi.org/project/optimuskg • Data: https://doi.org/10.7910/DVN/IYNGEV Highlights • A modern biomedical knowledge graph with molecular, anatomical, clinical, and environmental modalities. • Integrates 65 heterogeneous resources grounded with 18 ontologies and controlled vocabularies using the BioCypher framework and the Biolink Model. • Contains 190,531 nodes across 10 entity types, 21,813,816 edges across 27 relation types, and 67,249,863 property instances encoding 110,276,843 values across 150 distinct property keys. • Independently validated using PaperQA3, a multimodal agent that retrieves and reasons over scientific literature. • Reproducible, deterministic and infrastructure-agnostic data pipeline with parallel execution. • Distributed as Apache Parquet files and downloadable via the optimuskg python client. Do you think this might be an interesting initiative to showcase the use of Kedro in your website / documentation?

This is great, thank you so much for sharing! We love seeing Kedro used in such impactful research. We’ll take a look over the week and be in touch about next steps.

Perfect, thanks!

Wow thanks so much for sharing @lucas vittor! This is really awesome stuff 🔥