Sharing SRP data to reduce environmentally associated disease and promote transdisciplinary research

• Published in: Reviews on environmental health Vol. 35; no. 2; pp. 111 - 122
• Main Authors: Heacock, Michelle L., Amolegbe, Sara M., Skalla, Lesley A., Trottier, Brittany A., Carlin, Danielle J., Henry, Heather F., Lopez, Adeline R., Duncan, Christopher G., Lawler, Cindy P., Balshaw, David M., Suk, William A.
• Format: Journal Article
• Language: English
• Published: Germany De Gruyter 25.06.2020; Walter de Gruyter GmbH
• Subjects: Biomedical engineering; Data analysis; Data collection; Data integration; Data management; Data retrieval; data sharing; Data transmission; Engineering research; Environmental health; environmental health data; Environmental research; Environmental science; exposures and health; Information sharing; Pollution abatement; Public health; Questions; Research projects; Reuse; Superfund; transdisciplinary research; data integration; data sharing; transdisciplinary research; environmental health data; exposures and health
• ISSN: 0048-7554; 2191-0308; 2191-0308
• DOI: 10.1515/reveh-2019-0089

The National Institute of Environmental Health Sciences (NIEHS) Superfund Basic Research and Training Program (SRP) funds a wide range of projects that span biomedical, environmental sciences, and engineering research and generate a wealth of data resulting from hypothesis-driven research projects. Combining or integrating these diverse data offers an opportunity to uncover new scientific connections that can be used to gain a more comprehensive understanding of the interplay between exposures and health. Integrating and reusing data generated from individual research projects within the program requires harmonization of data workflows, ensuring consistent and robust practices in data stewardship, and embracing data sharing from the onset of data collection and analysis. We describe opportunities to leverage data within the SRP and current SRP efforts to advance data sharing and reuse, including by developing an SRP dataset library and fostering data integration through Data Management and Analysis Cores. We also discuss opportunities to improve public health by identifying parallels in the data captured from health and engineering research, layering data streams for a more comprehensive picture of exposures and disease, and using existing SRP research infrastructure to facilitate and foster data sharing. Importantly, we point out that while the SRP is in a unique position to exploit these opportunities, they can be employed across environmental health research. SRP research teams, which comprise cross-disciplinary scientists focused on similar research questions, are well positioned to use data to leverage previous findings and accelerate the pace of research. Incorporating data streams from different disciplines addressing similar questions can provide a broader understanding and uncover the answers to complex and discrete research questions.