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.
V. Alexiev. Workshop on Semantic Digital Archives (SDA 2012), part of International Conference on Theory and Practice of Digital Libraries (TPDL 2012), 912, Paphos, Cyprus, CEUR WS, (September 2012)
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)
A. P, V. Hariharan, R. Lavanya, and R. Prianka. International Journal of Innovative Science and Modern Engineering (IJISME), 3 (1):
16-18(December 2014)
M. Falis, H. Dong, A. Birch, and B. Alex. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, page 907--912. Online and Punta Cana, Dominican Republic, Association for Computational Linguistics, (November 2021)
P. Kathiria, and S. Ahluwalia. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 5 (1):
53 - 62(February 2016)