About GeoQuetzal
In 2025, I worked as a mentor for a group of undergraduate students in the Data Science for Public Good (DSPG) program at Iowa State University (ISU). During the program, we learned about R libraries that provide programmatic access to US Census data, as well as libraries for visualizing that data on maps. It was the first time I had worked with this kind of data, and it was remarkable how effectively it could communicate ideas and trends about the topics we were studying. I learned that these libraries were used in hundreds of academic, government, and industry research projects, giving researchers, professors, students, professionals, and map enthusiasts powerful tools for data analysis.
Inspired by that potential, I talked with Anasilvia about how important these tools are for research, and we were surprised to discover that no equivalent libraries existed for Guatemala, or for any other country in Central America. The semester ended and the idea stayed there, dormant but alive.
In 2026, we had to travel to Guatemala for administrative errands during Spring Break. While we were in our beautiful country, the idea resurfaced. We decided to tackle the project as a personal and meaningful hackathon: we knew the potential of the library, and we knew we could build it. In one week, with the help of Claude (the artificial intelligence from Anthropic), we planned, developed, and tested a proof of concept for both the Python and R libraries. The explicit use of generative AI as a development tool was a conscious decision that accelerated development and testing, and allowed us to complete the project in a very short timeframe.
After confirming that the libraries were both useful and feasible, we continued improving them, e.g., adding lugar poblado-level data, Voronoi polygons for sub-municipal choropleth mapping, bilingual documentation, and an examples website, with the goal of making map-based data analysis accessible to everyone interested in Guatemala.
Why does it matter?
Guatemala has millions of public data. The INE conducted a comprehensive census in 2018 covering more than 14 million people. MINFIN publishes the country’s administrative boundaries. But accessing that data programmatically, cleaning it, joining it, and visualizing it on a map required hours of manual work: downloading files, resolving name inconsistencies, writing code from scratch every time.
GeoQuetzal eliminates that friction. A few lines of code returns data ready to analyze or visualize.
We hope GeoQuetzal is useful for academic researchers, students, data journalists, government officials, and anyone curious about Guatemala. If you find a bug, have a suggestion, or want to contribute, the code is available on GitHub.
The authors
Jorge Yass is an online lecturer at Universidad del Valle de Guatemala (UVG) and a doctoral student in Human-Computer Interaction (HCI) at Iowa State University. 
Anasilvia Salazar is a lecturer at Universidad del Valle de Guatemala (UVG), where she teaches HCI courses, and a doctoral candidate in Human-Computer Interaction (HCI) at Iowa State University. 
Both share the conviction that data analysis tools should be accessible to everyone and that such access can potentiate investigation at technical and social levels to benefit society.