BACKGROUND -: Limited universally-adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison
this ultimately impedes the application of existing information-based tools to support advancement in diagnostics, treatments, and precision medicine. HYPOTHESIS/OBJECTIVES -: A single, coherent, logic-based standard for documenting breed names in health, production, and research-related records will improve data use capabilities in veterinary and comparative medicine. ANIMALS -: No live animals were used. METHODS -: The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence-readiness. RESULTS -: VBO is an open, community-driven ontology representing over 19,500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross-references to other databases. CONCLUSION AND CLINICAL IMPORTANCE -: The adoption of VBO as a source of standard breed names in databases and veterinary electronic health records can enhance veterinary data interoperability and computability.