OMOP2OBO Condition Occurrence Mappings V1.0 These mappings were created by the OMOP2OBO mapping algorithm (see links below). OMOP2OBO - the first health system-wide, disease-agnostic mappings between standardized clinical terminologies and eight Open Biomedical Ontology (OBO) Foundry ontologies spanning diseases, phenotypes, anatomical entities, cell types, organisms, chemicals, vaccines, and proteins. These mappings are also the first to be explicitly created using standard terminologies in the Observational Medical Outcomes (OMOP) common data model (CDM), ensuring both semantic and clinical interoperability across a space of N conditions (and N relationships curated in these ontologies). The mappings in this repository were created between OMOP standard condition occurrence concepts (i.e., SNOMED CT) to the Human Phenotype Ontology (HPO) and the (Mondo). The National Library of Medicine's Unified Medical Language System (UMLS) Semantic Types are first used to filter out all concepts that did not have a biological origin (accidents, injuries, external complications, and findings without clear interpretations). Then, the Semantic Type was used to prioritize the mapping of HPO concepts to findings and symptoms and Mondo to Semantic Types indicative of disease. For these OMOP domains, owl:intersectionOf (“and”), and owl:unionOf (“or”) constructors were used to construct semantically expressive mappings. Mapping Details Mappings included in this set were generated automatically using OMOP2OBO or through the use of a Bag-of-words embedding model using TF-IDF. Cosine similarity is used to compute similarity scores between all pairwise combinations of OMOP and OBO concepts and ancestor concepts. To improve the efficiency of this process, the algorithm searches only the top 𝑛 most similar results and keeps the top 75th percentile among all pairs with scores >= 0.25. Manually created mappings are also included. Mapping Categories Automatic Exact - Concept: Exact label or synonym, dbXRef, or expert validated mapping @ concept-level; 1:1 Automatic Exact - Ancestor: Exact label or synonym, dbXRef, or expert validated mapping @ concept ancestor-level; 1:1 Automatic Constructor - Concept: Exact label or synonym, dbXRef, cosine similarity, or expert validated mapping @ concept-level; 1:Many Automatic Constructor - Ancestor: Exact label or synonym, dbXRef, cosine similarity, or expert validated mapping @ concept-level; 1:Many Manual: Hand mapping created using expert suggested resources; 1:1 Manual Constructor: Hand mapping created using expert suggested resources; 1:Many Concept Similarity: score suggested mapping -- manually verified UnMapped: No suitable mapping or not mapped type Mapping Statistics Additional statistics have been provided for the mappings and are shown in the table below. This table presents the counts of OMOP concepts by mapping category and ontology: Mapping Category HPO Mondo Automatic Exact - Concept 4767 9097 Automatic Constructor - Concept 150 885 Concept Similarity 1374 667 Automatic Exact - Ancestor 13594 8911 Automatic Constructor - Ancestor 38085 40224 Manual 5119 755 Manual Constructor 10328 2835 Unmapped 36302 46345 Provenance and Versioning: The V1.0 deposited mappings were created by OMOP2OBO v1.0.0 on October 2022 using the OMOP Common Data Model V5.0 and OBO Foundry ontologies downloaded on September 14, 2020. Caveats: The deposited files only contain the mappings that were generated automatically by the algorithm. The manually generated mappings will be deposited with the official preprint manuscript. Please note that these are the original mappings that were created for the preprint. They have not been updated to current versions of the ontologies. In our experience, this should result in very few errors, but we do suggest that you check the ontology concepts used against current versions of each ontology before using them. Important Resources and Documentation GitHub: OMOP2OBO Project Wiki: OMOP2OBO - wiki Zenodo Community: OMOP2OBO Preprint Manuscript: 10.5281/zenodo.5716421