Related Experiment Video
Updated: Jan 13, 2026
05:47
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
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A general strategy for generating expert-guided, simplified views of ontologies
Anita R Caron1, Aleix Puig-Barbe2, Ellen M Quardokus3
1European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. caron.r.anita@gmail.com.
Scientific Data
|January 9, 2026
Summary
We developed tools to validate human-curated term hierarchies against ontology structures, ensuring FAIR data principles for biomedical research. These tools aid in resolving conflicts and improving data interoperability for cell atlases.
Area of Science:
- Biomedical Informatics
- Ontology Engineering
- Data Science
Background:
- Biomedical entity annotation using ontologies and tools ensures data Findability, Accessibility, Interoperability, and Reusability (FAIR).
- Standardized terms and ontology structures facilitate lexical search and biologically meaningful data grouping.
- Complex ontologies pose adoption barriers; manual simplifications in cell atlases may introduce unsuitable relationship types.
Purpose of the Study:
- To present tools for validating human expert-curated term hierarchies against established ontology structures.
- To support discussion and conflict resolution between human curation and ontological standards.
- To enhance the FAIRness of data within human reference atlas projects.
Main Methods:
- Development of validation tools for human expert-curated term hierarchies.
- Comparison of curated hierarchies against ontology structures, identifying matching and non-matching terms and relationships.
- Tabular statistics and graphical views to visualize validation results.
- Application and validation of tools within the HuBMAP Human Reference Atlas (HRA) and Human Developmental Cell Atlas projects.
Main Results:
- Tools successfully validate human expert-curated term hierarchies against ontology structures.
- Identification of discrepancies in terms and relationships between curated hierarchies and ontologies.
- Provision of detailed statistics and visualizations to facilitate conflict resolution.
- Demonstration of tool utility in real-world human reference atlas projects.
Conclusions:
- The developed tools effectively support the validation of curated hierarchies, promoting data standardization.
- These tools aid in resolving conflicts between manual curation and ontological standards, enhancing data interoperability.
- The approach improves the FAIRness of biomedical data, particularly within large-scale atlas initiatives.
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