On February 18, 2025 I had the pleasure of visiting National Taiwan University’s (NTU) in Taipei and leading a data visualization workshop at the Graduate Institute of Building and Planning.
The overall goal of the workshop was to 1) provide an overview of geospatial data and introduce working with this type of data in QGIS, 2) discuss theory and good practice for visualizing urban data for exploratory data analysis and communicating research to different audiences and 3) applying some of these techniques when creating maps in QGIS.
There were about 25 attendees, most of whom were graduate students interested in using GIS and data visualization for their research. All the workshop material, including slides and data, are available on this GitHub repository.
For the first hands-on part of the workshop, we played with a broad set of physical and built environment data (water, land use, streets, points of interest, etc.) from OpenStreetMap and Overture Maps to make general reference maps of Taipei. This included thinking about how to style individual data layers (e.g. colour, line width, etc.), layer data, and think about visual hierarchy. Here’s one output of playing with this data showing the density of businesses, landmarks, and public services in Taipei.
We also covered how to style based on different categories in a single data layer (e.g. for a data layer indicating land cover, having the forested area be one colour, wetlands be another colour, etc.) as well as filtering data to only show certain types of features.
For example, in the map below, we filtered the dataset in the map shown above to only visualize ice cream and shaved ice shops in Taipei.
We then dove into more data-driven visualization techniques; specifically creating choropleth maps – maps where data are coloured based on their numeric values – to help uncover and show patterns in quantitative data. Here are the two maps that we created: the first on population density for districts within Taipei City, and the second an air pollution map of Taiwan.
That was it for the formal part of the workshop. The remaining time was devoted to helping students think about visualizing their own data to aid their research goals, with several of the students working specifically on issues of land development, property values, and proposed changes in zoning and the impacts of these on gentrification and displacement.
Some of the material I created for this workshop was adapted for other workshops I led in conjunction with School of Cities India, and the material will be further tailored to incorporate into the visualization modules in our future educational offerings . Stay tuned for more!
