Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data
This work provides a scalable and interactive toolbox for nonspecialists to explore high-dimensional data, though it is incremental as it builds on the existing mapper algorithm with improvements in speed and usability.
The authors tackled the challenge of making the mapper algorithm from topological data analysis more accessible and efficient for high-dimensional data exploration, resulting in a web-based framework that computes mapper graphs for 1 million points of 256 dimensions in about 3 minutes, which is 4 times faster than the vanilla implementation.
The mapper algorithm is a popular tool from topological data analysis for extracting topological summaries of high-dimensional datasets. In this paper, we present Mapper Interactive, a web-based framework for the interactive analysis and visualization of high-dimensional point cloud data. It implements the mapper algorithm in an interactive, scalable, and easily extendable way, thus supporting practical data analysis. In particular, its command-line API can compute mapper graphs for 1 million points of 256 dimensions in about 3 minutes (4 times faster than the vanilla implementation). Its visual interface allows on-the-fly computation and manipulation of the mapper graph based on user-specified parameters and supports the addition of new analysis modules with a few lines of code. Mapper Interactive makes the mapper algorithm accessible to nonspecialists and accelerates topological analytics workflows.