On GIS and the Digital Humanities
I have been trained in data management, visualization, and spatial analysis methods which can be applied to research projects across disciplines, ranging from environmental science to urban planning. My academic background and passion remain in the humanities, though; so in future work, I am most excited to explore the application of GIS and data visualization tools to projects which could be lumped into the field of Digital Humanities.
Digital Humanities (DH) as a “field” is characterized by its focus on critical theory in light of rapidly evolving computational technology and big data. It’s a two-way street: What can computation tell us about the limits of critical theory? And what does critical theory tell us about our current systems of computation?
DH, like GIS, is thus emphatically transdisciplinary. Conducting research or building projects in DH depends on the careful implementation of computational workflows, which might include scripting for data processing, database design, UI/UX design, AR/VR, or webmapping. Through the course of my graduate study in GIS and DH at UCLA, I’ve grown particularly comfortable with scripting for geospatial applications with Python, relational database management with PostgreSQL, and webmapping with JavaScript.
With these skills refined, I am most excited to see and contribute to the development of DH projects which add to the pedagogical potential of library resources. By this, I mean that I am eager to make maps which can help users and researchers explore library catalogs spatially, through employment of objects’ geographic metadata. For example, the Discography of American Historical Recordings website features a map of places where sound recordings were captured, and I’ve disaggregated its data to show a more granular view of recording hotspots in the early twentieth century. For me, these tools add even greater value to a digital library resource which is already engaging.
I am also eager to explore or critique the pedagogical value of data visualization and exploration tools for the study of the history of urban space. I’m interested in working with more Time Series data to animate the development of demographic or cultural trends over the course of history, using census data, for example. I completed my first Time Series maps with data on migration from the Italian National Institute of Statistics (aggis.org/maps/istat; aggis.org/maps/unit5; for UCLA DH201, Winter 2024).
I think that visualizations like these need to be made carefully—a problematic dataset or processing error could result in the erasure of history, which ultimately accounts for misrepresentation. Nonetheless, a well-designed tool can help another user explore a vast historical database for which they might not otherwise have the know-how to query. To this end, I am interested in exploring open-source software development for the sake of democratizing GIS and data analysis tools.
