Abstract: What actions can we take to foster diverse and inclusive workplaces in the broad fields around data science? This paper reports from a discussion in which researchers from many different disciplines and departments raised questions and shared their experiences with various aspects around diversity, inclusion, and equity. The issues we discuss include fostering inclusive interpersonal and small group dynamics, rules and codes of conduct, increasing diversity in less-representative groups and disciplines, organizing events for diversity and inclusion, and long-term efforts to champion change.
Recommended citation: R. Stuart Geiger, Orianna DeMasi, Aaron Culich, Andreas Zoglauer, Diya Das, Fernando Hoces de la Guardia, Kellie Ottoboni, Marsha Fenner, Nelle Varoquaux, Rebecca Barter, Richard Barnes, Sara Stoudt, Stacey Dorton, Stéfan van der Walt. “Best Practices for Fostering Diversity and Inclusion in Data Science: Report from the BIDS Best Practices in Data Science Series.” BIDS Best Practices in Data Science Series. Berkeley, CA: Berkeley Institute for Data Science. 2019. doi:10.31235/osf.io/8gsjz