This presentation derives from a proposed awarded grant to form a cross-institutional, interdisciplinary working group of faculty and graduate students who research and teach with data in different domains—Gender and Border literature, English literature, American Studies, and Information Science—and who all share common training and investment in the humanities. The team will collaboratively work to revise undergraduate courses related to socially responsible computing in the humanities and information science, and each will each and publish one “responsible dataset in context”— an interesting, meaningful cultural dataset that is richly documented with the data’s social and historical context, and that is also accompanied by sample lessons plans and class exercises for how the data can be used in undergraduate computing or data studies classes.
The undergraduate course taught at UTSA is titled: Gender Violence at the Border through Literature, Data and Visualizations. Students will explore and critically analyze a selected group of border women’s literature text, archival material, oral histories and a database of counterdata that address gender-based and related violence and feminicides at the US-Mexico border. Through a close and distant reading analysis students will enhance in the development of multilingual geohumanities datasets to explore a series of thematically feminist visualizatons through transnational, intersectional, antiracist, geographical and historical frameworks. Additionally, students will explore various methods and digital tools and software with public datasets to convert these excerpts into critical multilingual datasets to develop a series of informative critical data visualizations.
The purpose of this project is to develop pedagogical resources that will help undergraduate students consider both the human decisions and sociohistorical contexts that impact the collection, categorization, and preservation of data, and to help them meaningfully incorporate this information into all subsequent analyses and interpretations of data. If we want our students to become responsible designers, engineers, and technologists, and to build more trustworthy and less harmful technological systems, then they need to learn to consider and incorporate the context of data into every step of the data science or computing process. We will be curating datasets that are focused on particular subject areas and domains, we plan to design our lesson plans in ways that broadly emphasize the importance of critical approaches to data, especially
antiracist, feminist, and decolonial approaches.