Due: 9/24
"Data are always collected for a specific purpose, by a combination of people, technology, money, commerce, and government." (Kurgan 2013, 35)
What
Find two datasets about a place you know, join or overlay them in Python, and make one map that says something neither dataset was collected to say.
Write two sentences of gallery text for it.
Requirements
- The place you select must be somewhere that you have lived and/or spent a significant enough amount of time to know something about lived experience there. It does not have to be New York City.
- Two datasets. At least one must be spatial (a shapefile, GeoJSON, GeoPackage, or a CSV with coordinates); the other can be tabular. At least one must not be from the tutorial.
- Investigate the origins of your two datasets. Some starting points to cover (at a minimum): who made the data? what is/was the intended use(s) of the data? when was the data made? how was it made? This goes in the description.
- Do the work in a notebook, the way Tutorial 2 did. Include a link to the notebook in your description (in Colab:
Share> anyone with the link can view). - Use an appropriate projected coordinate reference system for your place, and say which one.
- A designed composition on a single 16:9 page, with a title, a legend, a scale, a north arrow (north doesn't have to point up...), citations for both datasets, the projection, and your name. Altair gets you most of the way; finish in whatever you like.
- As you design your map choose one of the projects we have looked at thus far in class as a visual precedent, and imitate some aspect of its graphic style. Say which one.
Either way, submit:
- the map, as a PNG or a single-page PDF
- a two-sentence gallery text
- in the description: the two sources, what each was collected for, what you are using it for instead, the projection, the precedent, and the notebook link
Submission
Submit your work below. It appears under Student Work. Graded on completion. Your map does not have to provide answers - but can rather ask more precise questions.
Starting points
- Columbia Library Geodata Portal
- NYC Open Data, and the equivalent city or state portal wherever you are
- University mapping and research centers, for example Eviction Lab or the Beirut Urban Lab
- A rule of thumb: think about who would have the motivation and the money to make the dataset you want, then look for that entity.
- The data sources page collects what the tutorials use.
