The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization

Area of Science:

• Veterinary Medicine
• Bioinformatics
• Ontology Development

Background:

• Lack of universal data standards in veterinary medicine hinders interoperability and data integration.
• This limitation impedes the advancement of diagnostics, treatments, and precision medicine.

Purpose of the Study:

• To establish a logic-based standard for documenting vertebrate breed names.
• Improve data utilization in veterinary and comparative medicine through a unified breed nomenclature.

Main Methods:

• Developed the Vertebrate Breed Ontology (VBO) using data from global organizations, registries, and experts.
• Employed manual and computational methods to compile breed information and metadata.
• Classified VBO terms using description logic for AI compatibility.

Main Results:

• VBO includes over 19,500 livestock and companion animal breed concepts across 49 species.
• Breeds are classified by community/expert conventions and linked to NCBI Taxonomy.
• VBO metadata includes synonyms, identifiers, and cross-references, supporting advanced analytics.

Conclusions:

• Adoption of VBO as a standard enhances veterinary data interoperability and computability.
• Facilitates the application of information-based tools for precision medicine in veterinary health records.