This article describes efforts at the National Institutes of Health (NIH) from 2013 to 2016 to train a national workforce in biomedical data science. We provide an analysis of the Big Data to Knowledge (BD2K) training program strengths and weaknesses with an eye toward future directions aimed at any funder and potential funding recipient worldwide. The focus is on extramurally funded programs that have a national or international impact rather than the training of NIH staff, which was addressed by the NIH’s internal Data Science Workforce Development Center. From its inception, the major goal of BD2K was to narrow the gap between needed and existing biomedical data science skills. As biomedical research increasingly relies on computational, mathematical, and statistical thinking, supporting the training and education of the workforce of tomorrow requires new emphases on analytical skills. From 2013 to 2016, BD2K jump-started training in this area for all levels, from graduate students to senior researchers.

本文介绍了2013年至2016年美国国立卫生研究院（NIH）为培训国家生物医学数据科学工作人员所做的努力。我们对大数据知识（BD2K）培训计划的优缺点进行了分析，着眼于面向全球任何资助者和潜在资助接受者的未来方向。NIH的内部数据科学劳动力发展中心致力于解决由国家或国际影响的，由国家或国际影响的，由校外资助的计划，而不是对NIH员工进行培训。从一开始，BD2K的主要目标就是缩小所需和现有生物医学数据科学技能之间的差距。随着生物医学研究越来越依赖于计算，数学和统计思维，支持未来劳动力的培训和教育需要新的分析技能重点。从2013年到2016年，BD2K在该领域开始了从研究生到高级研究人员的各个级别的培训。