• Stephen J Mooney and Vikas Pejaver.
• Harborview Injury Prevention and Research Center, University of Washington, Seattle, Washington 98122, USA; email: sjm2186@uw.edu.
• Annu Rev Public Health. 2018 Apr 1; 39: 95-112.

AbstractThe digital world is generating data at a staggering and still increasing rate. While these "big data" have unlocked novel opportunities to understand public health, they hold still greater potential for research and practice. This review explores several key issues that have arisen around big data. First, we propose a taxonomy of sources of big data to clarify terminology and identify threads common across some subtypes of big data. Next, we consider common public health research and practice uses for big data, including surveillance, hypothesis-generating research, and causal inference, while exploring the role that machine learning may play in each use. We then consider the ethical implications of the big data revolution with particular emphasis on maintaining appropriate care for privacy in a world in which technology is rapidly changing social norms regarding the need for (and even the meaning of) privacy. Finally, we make suggestions regarding structuring teams and training to succeed in working with big data in research and practice.

15 keywords...

hide…