  Background: Limited universally adopted data standards in veterinary science
hinders data interoperability and therefore integration and comparison; this
ultimately impedes application of existing information-based tools to support
advancement in veterinary diagnostics, treatments, and precision medicine.
  Objectives: Creation of a Vertebrate Breed Ontology (VBO) as a single,
coherent logic-based standard for documenting breed names in animal health,
production and research-related records will improve data use capabilities in
veterinary and comparative medicine.
  Animals: No live animals were used in this study.
  Methods: A list of breed names and related information was compiled from
relevant sources, organizations, communities, and experts using manual and
computational approaches to create VBO. Each breed is represented by a VBO term
that includes all provenance and the breed's related information 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 19,000
livestock and companion animal breeds covering 41 species. Breeds are
classified based on community and expert conventions (e.g., horse breed, cattle
breed). This classification is supported by relations to the breeds' genus and
species indicated by 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 common names and
synonyms, breed identifiers or codes, and attributed cross-references to other
databases.
  Conclusion and clinical importance: Veterinary data interoperability and
computability can be enhanced by the adoption of VBO as a source of standard
breed names in databases and veterinary electronic health records.
