Methodology
1. Data Download (October 9, 2024):
2. Data Preparation:
Using Python and the Pandas library, I matched each artwork from the "Permanent Art Catalog" with its respective station coordinates (latitude and longitude) from the "Subway Stations" dataset. This process enabled us to link each artwork to the precise geographic location of its station.
3. Creation of the Interactive Map:
Using Python's Folium library, an interactive map was generated to display the artworks available across the New York subway system.
- For each station, a pop-up window provides the station name, a link to the artwork’s page, the artwork’s title, artist, and date.
- Filterable layers allow users to view artworks by decade, giving a chronological perspective on the evolution of public art in the subway network.
Development Ideas
- It would be great to include information about visible artworks at the departure, transfer, and arrival stations when calculating a journey on the app.
- We could develop an application that lets users "collect" artworks they've seen, similar to the FlashInvaders app.
- Another idea would be to introduce stamps or embossers near each station, allowing users to mark artworks they've visited in a special notebook, which could be sold by the MTA. This practice is popular in Japanese train stations (reference).