Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation...

Area of Science:

• Biomedical Informatics
• Artificial Intelligence
• Data Science

Background:

• The FAIR Guiding Principles emphasize data Findability, Accessibility, Interoperability, and Reusability.
• Ontologies are crucial for data integration, sharing, and analysis, especially with the proliferation of ontologies in the AI era.
• Interoperable ontologies are essential for standardized data presentation, knowledge representation, and reasoning.

Purpose of the Study:

• To introduce the eXtensible ontology development (XOD) strategy for creating interoperable ontologies.
• To demonstrate the application of the XOD strategy in developing the Coronavirus Infectious Disease Ontology (CIDO).
• To highlight the applications of interoperable ontologies in scientific research.

Main Methods:

• The XOD strategy is based on four principles: ontology term reuse, semantic alignment, ontology design pattern usage, and community extensibility.
• Software tools are available to facilitate the implementation of XOD principles.
• The XOD strategy was applied to develop the interoperable Coronavirus Infectious Disease Ontology (CIDO).

Main Results:

• The XOD strategy provides a framework for developing interoperable ontologies.
• The Coronavirus Infectious Disease Ontology (CIDO) was successfully developed using the XOD strategy.
• Interoperable ontologies, exemplified by CIDO, have diverse applications in fields like COVID-19 research and kidney precision medicine.

Conclusions:

• The XOD strategy is an effective approach for building interoperable ontologies.
• Interoperable ontologies are vital for advancing data standardization and knowledge discovery.
• The development and application of ontologies like CIDO support critical research areas and data sharing initiatives.