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BDIViz: An Interactive Visualization System for Biomedical Schema Matching with LLM-Powered Validation.

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    BDIViz streamlines biomedical data schema matching using interactive visualizations and LLM validation. This novel system improves accuracy and reduces curation time for complex datasets.

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    Area of Science:

    • Biomedical Informatics
    • Data Science
    • Human-Computer Interaction

    Background:

    • Biomedical data harmonization is crucial for research but schema matching is difficult.
    • Current automated methods struggle with accuracy on complex biomedical schemas.
    • Manual schema matching is time-consuming and prone to errors.

    Purpose of the Study:

    • To develop a novel visual analytics system, BDIViz, to streamline biomedical data schema matching.
    • To address scalability and semantic ambiguity challenges in schema matching.
    • To improve the efficiency and accuracy of matching disparate biomedical datasets.

    Main Methods:

    • Developed BDIViz, an interactive visual analytics system incorporating user-centered design.
    • Employed an ensemble approach combining multiple matching methods with LLM-based validation.
    • Utilized interactive heatmaps and coordinated views for efficient attribute comparison.

    Main Results:

    • BDIViz significantly improves schema matching accuracy compared to baseline methods.
    • The system reduces cognitive load and curation time for domain experts.
    • User studies demonstrated the effectiveness of BDIViz in two biomedical case studies.

    Conclusions:

    • BDIViz offers an effective solution for the challenging task of biomedical data schema matching.
    • Interactive visualization and ensemble methods enhance accuracy and usability.
    • The system facilitates more efficient exploratory analyses and meta-studies in biomedicine.