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RDA/US Chair Co-Authors Gender Diversity Article with NIH Associate Director

Francine Berman, chair of the U.S. branch of the Research Data Alliance and the Rensselaer Polytechnic Institute Edward G. Hamilton Distinguished Chair in Computer Science, is featured in the July 27 issue of the open access journal PLOS Biology in an article titled “Let’s Make Gender Diversity in Data Science a Priority Right from the Start.” Co-authored with Philip Bourne, associate director for data science at the National Institutes of Health, the article discusses the gender gap in STEM (science, technology, engineering, and mathematics) fields, where only 13 percent of the engineering workforce and 25 percent of the computer and mathematical sciences workforce are women, and the potential for the field of data science to narrow this gap and set a new bar for inclusion.  

Berman and Bourne advocate for gender diversity within data science, an emerging and fast-growing field in STEM, through attention to culture and proactive recruitment.

“Data science is critical for 21st century innovation,” said Berman. “It also provides an opportunity to create a STEM culture that maximizes its impact by being welcoming to all.”

The authors propose a multipronged approach: Inclusion of data science in STEM curricula and recruitment of women to careers in data science, positive social messages that indicate that it’s cool for women to be good at data science, and awareness of creating professional cultures in data science that are supportive of women.

“There are spectacular women who are thriving in data science careers, but their achievements are still overshadowed by pervasive stereotypes about working in the computational sciences,” said Bourne. “We need to counteract this impression and show young women that data science holds great opportunities for them too. To meet national priorities, we need both sexes to engage in data science; we need to get to the point where women data scientists are the norm rather than the exception.”

Culture change and new opportunities emerge from the individual actions of many. Berman and Bourne give “10 simple rules” for increasing gender diversity in data science that focus on evolution of organizational culture as well as individual action. They invite readers to add 10 of their own.

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