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Scientific Visualization and Data Integrity

scientific-visualization

K-Dense-AI/scientific-agent-skills

This skill guides the creation and auditing of truthful, accessible, and publication-ready scientific figures. It emphasizes maintaining data integrity by separating universal scientific principles from journal-specific rules. Users learn proper encoding (e.g., using position on common scales, handling uncertainty/missing data) and implementing designs with scope-aware Python libraries like Matplotlib and Seaborn, ensuring compliance with WCAG standards and maximizing scientific rigor.

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