Life course of retrospective harmonization initiatives: key elements to consider

Area of Science:

• Epidemiology
• Biostatistics
• Data Science

Background:

• Optimizing research on the developmental origins of health and disease (DOHaD) necessitates maximizing cohort study data utilization.
• Key requirements include sufficient statistical power for subgroup analysis and data with adequate follow-up and exposure heterogeneity.

Purpose of the Study:

• To outline the 'life course' of research projects that require data harmonization.
• To highlight critical elements for successful data harmonization in DOHaD research from inception to completion.

Main Methods:

• Emphasizes the need for cohort data to be findable, accessible, interoperable, and reusable (FAIR).
• Focuses on data harmonization to improve comparability across different studies and measures.
• Addresses challenges in collating, understanding, processing, hosting, and co-analyzing diverse cohort data.

Main Results:

• Harmonization is crucial for achieving comparability of measures collected across different DOHaD studies.
• Successful research initiatives depend on effective data management and analysis strategies.
• Identifies common issues faced by projects generating and using harmonized data.

Conclusions:

• Effective data harmonization and adherence to FAIR principles are essential for advancing DOHaD research.
• Addressing the complexities of data collation and analysis facilitates scientific success and timely project management.
• A comprehensive understanding of the data harmonization lifecycle supports robust and reproducible research outcomes.