The Vertebrate Breed Ontology: Towards Effective Breed Data Standardization
Kathleen R. Mullen (1), Imke Tammen (2), Nicolas A. Matentzoglu (3), Marius Mather (4), James P. Balhoff (5), Elizabeth Esdaile (6), Gregoire Leroy (7), Carissa A. Park (8), Halie M. Rando (9), Nadia T. Saklou (10), Tracy L. Webb (10), Nicole A. Vasilevsky (11)

TL;DR
The Vertebrate Breed Ontology (VBO) provides a comprehensive, logic-based standard for breed data, enhancing interoperability and AI-readiness in veterinary and comparative medicine.
Contribution
This paper introduces the VBO, a large, community-driven, logic-based ontology for breed data covering over 19,500 breeds across 49 species, supporting data standardization and advanced analytics.
Findings
VBO includes over 19,500 breed concepts across 49 species.
Breeds are classified using description logic and linked to NCBI taxonomy.
Relationships and metadata support advanced data analytics and interoperability.
Abstract
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. 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. 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…
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Taxonomy
MethodsOntology
