Broadening participation in environmental data science: Insights from practitioners

Abstract Environmental data science (EDS) is a nascent STEM sub-discipline where we have the opportunity to shape the culture, to work to create an environment that welcomes broad participation, and to build a culture of inclusivity. Like many STEM disciplines, some may be excluded from participating in EDS due to historical legacies, systemic barriers, and social prejudices that create unequal opportunities and access. To better understand barriers to participation, and to identify solutions and priorities, we conducted a survey of the participants of the first Environmental Data Science Summit. We identified three barriers to participation that matched with three solutions and priorities for the field. The most commonly identified barrier was an unsupportive work environment for minorities and a male-dominated culture; creating a supportive community and work environment, particularly for minorities, was identified as both a solution and a priority for broadening participation in EDS. The second most commonly identified barrier pertained to training and maintaining relevance— specifically, late or informal training experiences and time constraints limiting time to upskill. The