Let's Make Gender Diversity in Data Science a Priority Right from the Start

PLoS Biol. 2015 Jul 27;13(7):e1002206. doi: 10.1371/journal.pbio.1002206. eCollection 2015 Jul.

Abstract

The emergent field of data science is a critical driver for innovation in all sectors, a focus of tremendous workforce development, and an area of increasing importance within science, technology, engineering, and math (STEM). In all of its aspects, data science has the potential to narrow the gender gap and set a new bar for inclusion. To evolve data science in a way that promotes gender diversity, we must address two challenges: (1) how to increase the number of women acquiring skills and working in data science and (2) how to evolve organizations and professional cultures to better retain and advance women in data science. Everyone can contribute.

MeSH terms

  • Female
  • Humans
  • Informatics*
  • Organizational Culture
  • Sexism / prevention & control*
  • Women

Grants and funding

The authors received no specific funding for this work.