Data Readiness

Data readiness, crucial for effective AI, focuses on ensuring data quality and suitability for AI applications. Current research emphasizes quantitative assessment frameworks, visual analysis techniques for understanding data context, and the development of standardized metrics across diverse data types (structured, unstructured, multilingual). This work aims to improve AI model accuracy, fairness, and trustworthiness, impacting both the development of robust AI systems and the responsible use of data in various fields, including healthcare and scientific research.