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.
M. Glauer, T. Mossakowski, F. Neuhaus, A. Memariani, and J. Hastings. A Compendium of Neuro-Symbolic Artificial Intelligence, volume 369 of Frontiers in Artificial Intelligence and Applications, chapter 21, IOS press, (2023)
M. Glauer, F. Neuhaus, T. Mossakowski, and J. Hastings. German conference on artificial intelligence 2023, volume 14236 of Lecture Notes in Artificial Intelligence, page 31-45. Springer, (2023)Best paper award. Also available at https://doi.org/10.48550/arXiv.2301.08577.
E. Ilkou, H. Abu-Rasheed, M. Tavakoli, S. Hakimov, G. Kismihók, S. Auer, and W. Nejdl. The Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24-28, 2021, Proceedings, volume 12922 of Lecture Notes in Computer Science, page 546--562. Springer, (2021)
A. Memariani, M. Glauer, F. Neuhaus, T. Mossakowski, and J. Hastings. International Workshop on Data meets Applied Ontologies in Explainable AI (DAO-XAI 2021), volume 2998 of CEUR Workshop Proceedings, http://ceur-ws.org/Vol-2998/, (2021)