VO: The Vaccine Ontology

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.