Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data
Youjia Zhou, Nithin Chalapathi, Archit Rathore, Yaodong Zhao, Bei Wang

TL;DR
Mapper Interactive is a web-based, scalable, and extendable tool that enables interactive topological analysis and visualization of high-dimensional data, significantly improving speed and usability for large datasets.
Contribution
It introduces a scalable, user-friendly framework for the mapper algorithm, supporting large datasets and easy extension, enhancing practical topological data analysis.
Findings
Supports analysis of 1 million points in 256 dimensions in about 3 minutes
Provides an interactive visual interface for real-time graph manipulation
Enables easy addition of new analysis modules with minimal code
Abstract
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…
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Taxonomy
TopicsTopological and Geometric Data Analysis · Data Visualization and Analytics · Digital Image Processing Techniques
