Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching

The purpose of these datasets is to support <em>equivalence</em> and <em>subsumption</em> ontology matching. There are five ontology pairs extracted from MONDO and UMLS: <strong>Source</strong> <strong>Ontology Pair</strong> <strong>Category</strong> MONDO OMIM-ORDO Disease MONDO NCIT-DOID Disease UMLS SNOMED-FMA Body UMLS SNOMED-NCIT Pharm UMLS SNOMED-NCIT Neoplas Each pair is associated with three folders: "raw_data", "equiv_match", and "subs_match", corresponding to the downloaded source ontologies, the package for equivalence matching, and the package for subsumption matching. See detailed instructions at: https://krr-oxford.github.io/DeepOnto/#/om_resources. See the incoming OAEI Bio-ML track at: https://www.cs.ox.ac.uk/isg/projects/ConCur/oaei/. See our resource paper at: https://arxiv.org/abs/2205.03447. Please use the most recent version as the instructions are updated accordingly.