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Current Epidemiology Reports

, Volume 6, Issue 3, pp 291–299 | Cite as

Data Science in Environmental Health Research

  • Christine Choirat
  • Danielle Braun
  • Marianthi-Anna KioumourtzoglouEmail author
Environmental Epidemiology (F Laden and J Hart, Section Editors)
  • 52 Downloads
Part of the following topical collections:
  1. Topical Collection on Environmental Epidemiology

Abstract

Purpose of Review

Data science is an exploding trans-disciplinary field that aims to harness the power of data to gain information or insights on researcher-defined topics of interest. In this paper, we review how data science can help advance environmental health research.

Recent Findings

We discuss the concepts of computationally scalable handling of big data and the design of efficient research data platforms and how data science can provide solutions for methodological challenges in environmental health research, such as high-dimensional outcomes and exposures and prediction models. Finally, we discuss tools for reproducible research.

Summary

In this paper, we present opportunities to improve environmental research capabilities by embracing data science and the pitfalls that environmental health researchers should avoid when employing data scientific approaches. Throughout the paper, we emphasize the need for environmental health researchers to collaborate more closely with biostatisticians and data scientists to ensure robust and interpretable results.

Keywords

Data science Big data Environmental health research Reproducibility Environmental mixtures High-dimensional Research data platforms 

Notes

Funding Information

This work was supported by NIEHS P30 ES009089 and R01 ES028805. This work was partially supported by HEI grant 4953-RFA14-3/16-4; the Health Effects Institute (HEI) is an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No.CR-83467701) and certain motor vehicle and engine manufacturers.

Compliance with Ethical Standards

Conflict of Interest

The authors declare no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by the authors.

Disclaimer

The contents of this article do not necessarily reflect the views of HEI, or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Christine Choirat
    • 1
  • Danielle Braun
    • 2
    • 3
  • Marianthi-Anna Kioumourtzoglou
    • 4
    Email author
  1. 1.Swiss Data Science CenterETH Zurich and EPFLZurichSwitzerland
  2. 2.Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonUSA
  3. 3.Department of Data SciencesDana-Farber Cancer InstituteBostonUSA
  4. 4.Department of Environmental Health SciencesColumbia University Mailman School of Public HealthNew YorkUSA

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