Data Quality, Harmonization, and FAIR Data Readiness

What this project does
Ensures that HADRC data are standardized, well-annotated, and ready for reuse and analysis.

Why it matters clinically
High-quality, harmonized data reduce errors, improve reproducibility, and allow meaningful cross-study comparisons.

Key activities
-Curate and harmonize multimodal datasets using standardized data elements
-Apply consistent terminologies and ontologies
-Perform quality assurance and semantic enrichment
-Prepare de-identified datasets following FAIR principles

What will be delivered
-Well-annotated, analysis-ready datasets
-Data resources suitable for cross-center and longitudinal studies

Who this helps
-Investigators conducting secondary analyses
-Researchers integrating data across modalities and studies