CLUES A Comprehensive Workflow for Integrating Geospatial Data in Biomedical Research.

Area of Science:

• Environmental Health
• Biomedical Informatics
• Geospatial Science

Background:

• Integrating environmental exposure data into biomedical research is challenging due to technical complexity and data fragmentation.
• Understanding environmental influences on physical and mental health requires robust data linkage methods.

Purpose of the Study:

• To introduce the EnvironMENTAL Climate, Urbanicity, Environment and Society (CLUES) framework, an automated workflow for generating individual-level environmental exposure data.
• To evaluate the scalability, performance, and reproducibility of the CLUES framework for large-scale biomedical research.

Main Methods:

• CLUES automates the selection, download, and standardization of open-access geospatial datasets.
• It maps environmental variables (urbanicity, climate, pollution, socioeconomic factors) to individual-level biomedical data.
• The framework requires no prior geospatial expertise and supports global settings.

Main Results:

• The CLUES framework provides an end-to-end solution for multidimensional environmental exposure mapping.
• It demonstrates scalability and computational efficiency for large cohorts.
• The framework adheres to FAIR data principles and privacy-compliant data protection.

Conclusions:

• CLUES significantly reduces technical barriers to integrating environmental data in health research.
• The framework is extensible, applicable across diverse cohorts, and promotes reproducible research.
• CLUES facilitates a more comprehensive understanding of environmental determinants of health.