I mathematically mapped 4,000+ drinks across 22 sensory dimensions using UMAP [OC] Visualization

What This Visualization Shows

This data visualization displays "I mathematically mapped 4,000+ drinks across 22 sensory dimensions using UMAP [OC]" and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on Data Source: I compiled a corpus of professional beverage tasting notes and multilingual recipes. I then passed this unstructured text through Gemini, prompting it to act as a deterministic classifier to score each libation across a strict 22-dimension sensory ontology (measuring traits like acidity, umami, roast, and cooling menthol on a uniform scale).

Tools Used: I used UMAP for the dimensionality reduction to project the 22D vectors into a visualizable 3D space. The frontend is rendered in WebGL using Three.js, and it runs on a FastAPI + Supabase backend to handle the nearest-neighbor vector math.

Dynamic Mapping: The 22D vector space isn't static. I built a pipeline so that if a libation is missing, users can input the name, and the backend will run the LLM classification and UMAP/nearest-neighbor placement in real-time to generate a new node on the map.

Interesting Finding: Dimensionality reduction inherently forces macro-groupings: in this case, the UMAP algorithm naturally split the universe into alcoholic and non-alcoholic clusters.

However, if you use the "Wormhole" feature to run a raw 22-dimensional nearest-neighbor search, it bridges that gap. Nitro Cold Brew and Dry Stouts (like Guinness) turn out to be almost exact mathematical twins based on their underlying flavor vectors (roast, body, chocolate), even though they live in different 3D clusters.

If you want to pan around the galaxy or see what the mathematical neighbor of your favorite drink is, I hosted the live interactive 3D map here: https://elixir.wongqihan.com, which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

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Data Analysis and Insights

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