The translational aspects of data science — the analysis of big data — promise to benefit individuals, science and society. They stand to open up new lines of enquiry in computer science, statistics, ethics, data governance, cognitive psychology, organizational behaviour, information science, sociology and behavioural economics. With an overflowing treasure chest of big data, the time is ripe to tackle the crucial questions that can help translational data science to realize its potential (see, for example, go.nature.com/2nz2qzw and go.nature.com/2kjxa67).
Because it bridges the gap between foundational methods and practical application, translational data science stands to further the study of data-science methods (see D. Donoho J. Comp. Graph. Stats 26, 745–766; 2017). It should also democratize the data-science process and provide knowledge that can inform practical discourse among stakeholders (see also M. Zook et al. PLoS Comput. Biol. 13, e1005399; 2017).
Nature 561, 464 (2018)