Exploring Open Access Art Using the Deno Jupyter Kernel

This blog post explores using Deno's Jupyter kernel to analyze the National Gallery of Art's Open Access dataset, focusing on the interaction of JavaScript and TypeScript with data science techniques for exploring and visualizing artwork information. It provides insights into the dataset's structure, the process of cleaning and merging data, and deploying advanced data visualizations and interactions using libraries like Polars and Observable Plot.