The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization

Authors

• Kathleen R. Mullen, University of North Carolina at Chapel Hill
• Imke Tammen, The University of Sydney
• Nicholas A. Matentzoglu, Semanticly Ltd
• Marius Mather, The University of Sydney
• James P. Balhoff, University of North Carolina at Chapel Hill
• Elizabeth Esdaile, University of California, Davis
• Carissa A. Park, Iowa State University
• Halie M. Rando, Smith CollegeFollow
• Nadia T. Saklou, Colorado State University, Fort Collins
• Tracy L. Webb, Colorado State University, Fort Collins
• Nicole A. Vasilevsky, Critical Path Institute
• Christopher J. Mungall, Lawrence Berkeley National Laboratory
• Melissa A. Haendel, University of North Carolina at Chapel Hill
• Frank W. Nicholas, The University of Sydney
• Sabrina Toro, University of North Carolina at Chapel Hill

Author ORCID Identifier

Kathleen Mullen: 0000-0002-5002-8648

Imke Tammen: 0000-0002-5520-6597

Nicolas Matentzoglu: 0000-0002-7356-1779

Marius Mather: 0000-0002-3616-6235

James P. Balhoff: 0000-0002-8688-6599

Elizabeth Esdaile: 0000-0001-6238-9793

Gregoire Leroy: 0000-0003-2588-4431

Carissa A. Park: 0000-0002-2346-5201

Halie M Rando: 0000-0001-7688-1770

Nadia Saklou: 0000-0001-7894-3947

Tracy Webb: 0000-0003-4547-3787

Nicole Vasilevsky: 0000-0001-5208-3432

Christopher Mungall: 0000-0002-6601-2165

Melissa Anne Haendel: 0000-0001-9114-8737

Frank Nicholas: 0000-0002-9178-3965

Sabrina Toro: 0000-0002-4142-7153

Document Type

Article

Publication Date

2025

Publication Title

Journal of Veterinary Internal Medicine

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.

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.

Keywords

animal population groups, biological ontologies, breeding, genetics, precision medicine, theriogenology

Volume

39

First Page

e70133

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Rights

© 2025 The Author(s).

Version

Version of Record

Recommended Citation

Mullen, Kathleen R.; Tammen, Imke; Matentzoglu, Nicholas A.; Mather, Marius; Balhoff, James P.; Esdaile, Elizabeth; Park, Carissa A.; Rando, Halie M.; Saklou, Nadia T.; Webb, Tracy L.; Vasilevsky, Nicole A.; Mungall, Christopher J.; Haendel, Melissa A.; Nicholas, Frank W.; and Toro, Sabrina, "The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization" (2025). Computer Science: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/csc_facpubs/433