Published May 6, 2022
| Version Deprecated
Dataset
Open
Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching
- 1. University of Oxford
- 2. City, University of London
- 3. Samsung Research UK
Description
The purpose of these datasets is to support equivalence and subsumption ontology matching.
There are five ontology pairs extracted from MONDO and UMLS:
| Source | Ontology Pair | Category |
| 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 documentation 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.