GT DataWorks is an outreach program, an educational program, and a research platform. GT DataWorks employs young people from communities historically minoritized in computing and employs them as data wranglers. Drawing from informal learning programs, such as Glitch Game Testers, we leveraged principles of legitimate peripheral participation to develop a community of practice centered around work with data. The motivation for creating DataWorks is two-fold. The first was to create a model for training members of historically minoritized communities in entry-level data science skills as a pathway to long-term, full-time employment. The second motivation for creating DataWorks is to develop a workplace training model that supports sustained research into the contextual qualities of data science in an authentic work environment. Through these efforts, we have developed new approaches to data science that acknowledge and respect diverse subjectivities and do not just reproduce the white, male, heteronormative hegemony of data science.


  • Annabel Rothschild, Carl DiSalvo, and Betsy DiSalvo. 2021. "Towards a Community-Defined Framework for Responsible Digital Piecework Requests." Position paper in The Global Labours of AI and Data Intensive Systems workshop at CSCW 2021. PDF
  • Rothschild, Annabel, Carl DiSalvo, Amanda Meng, Ben Shapiro, Britney Johnson and Betsy DiSalvo (2022) "Interrogating Data Work as a Community of Practice." Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2). 
  • Johnson, Britney, Ben Rydal Shapiro, Betsy DiSalvo, Annabel Rothschild, and Carl DiSalvo (2021). "Exploring Approaches to Data Literacy Through a Critical Race Theory Perspective." In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1-15. (Honorable Mention Award)