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CLUES a comprehensive workflow for integrating geospatial data in biomedical research

Environmental exposures play a critical role in shaping physical and mental health, yet integrating such data into biomedical research remains technically complex and fragmented. The EnvironMENTAL Climate, Urbanicity, Environment and Society (CLUES) framework is an open-source, end-to-end workflow f...

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Autori principali: Jentsch, Marcel (Autore) , Polemiti, Elli (Autore) , Banaschewski, Tobias (Autore) , Christmann, Nina (Autore) , Holz, Nathalie E. (Autore) , Janson, Karina (Autore) , Meyer-Lindenberg, Andreas (Autore) , Schwarz, Emanuel (Autore)
Natura: Article (Journal)
Lingua:inglese
Pubblicazione: 13 May 2026
In: Nature Communications
Year: 2026, Volume: 17, Pages: 1-11
ISSN:2041-1723
DOI:10.1038/s41467-026-73048-6
Accesso online:Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41467-026-73048-6
Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41467-026-73048-6
Testo
Note sull'autore:Marcel Jentsch, Elli Polemiti, Tobias Banaschewski, Nina Christmann, Nathalie E. Holz, Karina Janson, Andreas Meyer-Lindenberg, Emanuel Schwarz [und viele weitere]
Descrizione
Riassunto:Environmental exposures play a critical role in shaping physical and mental health, yet integrating such data into biomedical research remains technically complex and fragmented. The EnvironMENTAL Climate, Urbanicity, Environment and Society (CLUES) framework is an open-source, end-to-end workflow for generating individual-level environmental exposure data. CLUES automates the selection and download of open-access geospatial datasets, standardises spatial and temporal formats, and maps projections, and links resulting environmental variables to individual-level biomedical data, requiring no prior expertise in geospatial data. CLUES covers key environmental domains, including urban and natural space, climate and weather extremes, air pollution, and regional socioeconomic conditions. Designed for extensibility and cross-cohort applicability, it enables multidimensional exposure mapping across global settings and adheres to FAIR (Findability, Accessibility, Interoperability and Reusability) and privacy-compliant data protection principles. In this work, we present the CLUES framework and evaluate its scalability, computational performance, and reproducibility for large-scale biomedical research.
Descrizione del documento:Gesehen am 17.09.2026
Descrizione fisica:Online Resource
ISSN:2041-1723
DOI:10.1038/s41467-026-73048-6

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