This project is a 3D data visualization of New York City restaurants, is all about culture, stories, and histories behind food and migration.

Context

In a society where polarization, extremization, pure nationalism, and racial discrimination are becoming increasingly serious, by revealing the history and culture behind food, it can help to bring communities back together.

Immigrant, Food and Space: New York City as a Hot Pot

New York City is like a microcosm of the world. Communities with various cultural backgrounds are interlaced and stationed in this cramped “space”. Communication and infusion between different communities have become an inevitable thing.

Moreover, it is not so much an active exchange between different cultures, but a bumping up against one another due to the density of the human space.

However, immigrants also bring a part of their own native culture to maintain their identity. Just like many births of fusion cuisines, traits remix and combine to make something new.

By revealing the pattern behind stories, people will understand that it is more complicated than the way they used to think about the links between people of different culture backgrounds.

Abstract 3D Data Visualization

When you remove the need of instrumentality, there is a kind of expressiveness comes up. My project is looking for a sweet spot between instrumentality and expressiveness.

In this design, I compiled the data of 457 restaurants in Manhattan. The source of the data is the Department of Health and Mental Hygiene (DOHMH) New York City Restaurant Inspection Results. This large and comprehensive database records every restaurant: Particularly, The name of the restaurant, street name, type of cuisine, sanitary inspection rating, latitude and longitude, administrative area and other information. A total of 40,000 individual records, for the convenience of statistics, all the restaurant records I selected are from March 2020, and this datasets excluded the geographical location of restaurants with incomplete location information are then divided into different categories based on different cuisines. A total of 14 categories: Indian, American, Asian, Caribbean, Chinese, French, Italian, Japanese, Jewish Kosher, Korean, Latin, Mexican, Spanish, Thai.

Final Version

Restaurants in March vs November 2020

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