Enhancing Data Integration, Interoperability, and Reuse to Address Complex and Emerging Environmental Health Problems

• Published in: Environmental science & technology Vol. 56; no. 12; pp. 7544 - 7552
• Main Authors: Heacock, Michelle L., Lopez, Adeline R., Amolegbe, Sara M., Carlin, Danielle J., Henry, Heather F., Trottier, Brittany A., Velasco, Maria L., Suk, William A.
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 21.06.2022
• Subjects: cooperative research; Data integration; Data retrieval; Data science; Data transmission; Environmental health; environmental science; Exposure; Hazardous materials; Health problems; Health sciences; human health; Interoperability; landscapes; Multidisciplinary research; Pollution abatement; research programs; Research projects; Superfund; Environmental Health Sciences; FAIR; Superfund Research Program; Data Integration; Data Interoperability
• ISSN: 0013-936X; 1520-5851; 1520-5851
• DOI: 10.1021/acs.est.1c08383

Environmental health sciences (EHS) span many diverse disciplines. Within the EHS community, the National Institute of Environmental Health Sciences Superfund Research Program (SRP) funds multidisciplinary research aimed to address pressing and complex issues on how people are exposed to hazardous substances and their related health consequences with the goal of identifying strategies to reduce exposures and protect human health. While disentangling the interrelationships that contribute to environmental exposures and their effects on human health over the course of life remains difficult, advances in data science and data sharing offer a path forward to explore data across disciplines to reveal new insights. Multidisciplinary SRP-funded teams are well-positioned to examine how to best integrate EHS data across diverse research domains to address multifaceted environmental health problems. As such, SRP supported collaborative research projects designed to foster and enhance the interoperability and reuse of diverse and complex data streams. This perspective synthesizes those experiences as a landscape view of the challenges identified while working to increase the FAIR-ness (Findable, Accessible, Interoperable, and Reusable) of EHS data and opportunities to address them.