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VO: The Vaccine Ontology.

Jie Zheng1, Asiyah Yu Lin1, Anthony Huffman1

  • 1University of Michigan, Ann Arbor, MI, USA.

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|April 30, 2026
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Summary

The Vaccine Ontology (VO) standardizes vaccine data for research and clinical use, enabling better data integration and AI-driven insights. This ontology aids in understanding diverse vaccine types and their applications.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Data Science

Background:

  • Standardizing vaccine data is crucial for FAIR data practices and computational analysis.
  • Existing vaccine information is fragmented across diverse types and resources.
  • Need for a computable model to support vaccine research and development.

Purpose of the Study:

  • To develop and maintain the Vaccine Ontology (VO) for standardized vaccine representation.
  • To integrate diverse vaccine information and support computer-assisted reasoning.
  • To align VO with established ontology principles (Basic Formal Ontology, OBO Foundry).

Main Methods:

  • Developed VO as a community-based ontology since 2007.
  • Modeled vaccines, components, immune responses, and studies.
  • Mapped VO to external resources (RxNorm, CVX, FDA, USDA).

Main Results:

  • VO represents over 10,000 vaccines for human and animal health.
  • Facilitates standardization in databases like VIOLIN, ImmPort, and VAC.
  • Enables semantic queries and enhances analysis of vaccine datasets and literature.

Conclusions:

  • VO provides a standardized model for vaccine data.
  • Supports advanced vaccine research, including AI applications in the Semantic Web.
  • Improves data integration and accessibility for vaccine information.