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 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.

翻译：背景：兽医学领域缺乏普遍采用的数据标准，这阻碍了数据互操作性，进而影响数据的整合与比较；最终限制了现有基于信息的工具在支持诊断、治疗和精准医学发展方面的应用。目标：建立一个单一、连贯、基于逻辑的标准，用于记录健康、生产和研究相关记录中的品种名称，将提升兽医学和比较医学领域的数据利用能力。方法：脊椎动物品种本体论（VBO）的创建基于从联合国粮食及农业组织、品种登记机构、社区和专家处汇编的品种名称及相关信息，采用了人工与计算相结合的方法。每个品种由一个VBO术语表示，该术语包含品种信息和来源作为元数据。VBO术语使用描述逻辑进行分类，以实现计算应用和人工智能就绪性。结果：VBO是一个开放的、社区驱动的本体论，代表了超过19,500个涵盖49个物种的家畜和伴侣动物品种概念。品种根据社区和专家惯例（例如，牛品种）进行分类，并通过与美国国家生物技术信息中心（NCBI）分类学术语关联的属种关系予以支持。VBO术语之间的关系（例如，将品种与其基础种群关联）提供了额外的上下文，以支持高级数据分析。VBO术语元数据包括同义词、品种标识符/代码以及指向其他数据库的归属交叉引用。结论与临床重要性：在数据库和兽医电子健康记录中采用VBO作为标准品种名称的来源，可以增强兽医数据的互操作性和可计算性。