Data Science JEDI
Justice, Equity, Diversity, Inclusion
While data science is a relatively new field, its roots are in computer science and statistics, two fields that have not been historically diverse. At ADSA, we strive to foster a welcoming and inclusive environment to promote diversity in the field of data science as a whole, and within our member community. Our commitment to JEDI starts with explicitly stating our values in our Mission, Vision, Values statement. These values are made actionable in our Code of Conduct, where we make explicit our expectations of behavior and language, and anyone made to feel unwelcome at any ADSA event (online or virtual) has a clear path to recourse.
We actively solicit keynote speakers, panelists, and participants from a diversity of backgrounds and institutions for all of our events. At our most recent in-person gathering (the 2022 Spring Meeting), 44% of attendee survey respondents identified as a race or ethnicity other than White and 44% identified as women (2 survey respondents preferred not to list their genders). To ensure the programming we offer during our annual meetings reflects the diversity of fields that make up data science (beyond statistics and computer science), we are intentional about the fields of study represented by our Program Committees (PC), as well as the demographics of the committee members. Taken together, the 2021/2022 program committees had a majority of women (13/20) and some racial diversity (6/20 non-White). The diversity of fields represented included: Astrophysics, Black Studies, Business Analytics, Computational Biology, Economics, Oceanography, and Political Science.
It is our full intention to continue to expand the reach of our organization to support people and institutions that represent the full diversity of our society. Toward that end, we have been actively engaging with Historically Black Colleges and Universities (HBCUs) and Tribal Colleges and Universities (TCUs) through our recently awarded NSF IUSE project.
Supporting Student Success in Environmental Data Science at Minority Serving Institutions
With funding from the NSF IUSE program, we are partnering with the Environmental Data Science Inclusion Network (EDSIN), the Carpentries, the Atlanta University Center Data Science Initiative, the Native BioData Consortium, the Center for Scientific Collaboration and Community Engagement (CSCCE), and Sara Bolduc Planning and Evaluation LLC (SBPE) to build a network of colleagues at Historically Black Colleges and Universities (HBCUs) and Tribal Colleges and Universities (TCUs) through monthly meetings and a series of mini-workshops. Our overarching goals are community building and co-creation of a set of recommendations for improving student success in environmental data science at these two institution types.
Specifically, this project seeks to bring together representatives from HBCUs, TCUs, and relevant organizations to build resource networks, identify assets and barriers to data science education, and co-create a set of recommendations for addressing barriers, focusing specifically on environmental sciences, thus empowering and supporting equitable data science education and training opportunities that ameliorate the digital divide. Paraphrasing our project Abstract, our project has the following goals: 1) identify the unique assets that HBCUs and TCUs bring to environmental data science education and any barriers to adoption, 2) identify and raise awareness of the resources and other assets available through existing organizations that support equitable data science education, 3) promote relationship-building among faculty and partner organizations, forming the basis of a network for future community-informed resource sharing; 4) co-develop a Recommendations Report that will enhance student success in environmental data science at these institutions. The project will build relationships across partners and concentrate activities on identifying shared solutions that can be adopted within a variety of contexts and scales, facilitating opportunities for continuous learning across groups.
We are grateful to all of the project participants and leadership for their time and commitment. Our networks have benefited from these many connections. Just one example: as part of our 2021/2022 virtual Annual Meeting, we were fortunate to host a panel discussion, led by Krystal Tsosie, exploring Community-Centered Benefit Sharing and New Data Equities (YouTube video).
Please Note: This material is based upon work supported by the National Science Foundation under Grant DUE-2135830. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.