Standard graph algorithms like PageRank and k-core decomposition can extract deeper insights from UMAP's internal k-nearest-neighbor graphs. This approach bypasses the distortion inherent in 2D projections by analyzing the original high-dimensional manifold. Apple researchers show this method identifies representative data points more accurately. Practitioners can now improve high-dimensional data sensemaking.