DAN MILLER

03 LOCATION INTELLIGENCE OTHERWISE

2023-2024

Location intelligence companies have adopted the lexicon of human geography, even if their products have a very thin relationship to the full breadth of geographic inquiry. One prominent product, and the center of my capstone project for the Computational Design Practices program at GSAPP, are Points or Places of Interest data or POI. At a minimum, POI are locations, mappable to coordinates, that web map users can generally visit. They are most often retail stores, restaurants, parks or institutions, but can also represent events. Information about these locations can vary between datasets, but they generally reflect location, contact information, and function or place category (store, restaurant, landmark, atm, commercial or public place).

This is a very limited lens through which to view and represent the complexity and many scales of place. And those limitations are cause for concern given the prevalence, influence, and power that location intelligence products that produce POIs have in structuring the physical world and our relationships to it. The discourse on the differences between space, place, and representations of the two in geography is complex – what I am most interested in is recovering the experiential and difficult-to-map aspects of place within our digital systems, and trying to create alternate systems for relating to places, and representing them, at scale.

Collaborators:

Tools:
Link:

Advisor: Josh Begley
Capstone Instructor: Seth Thompson
Python, HTML, CSS, JavaScript, MapLibre
https://mappingproblems.github.io/places

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