# DataMap: A Portable Application for Visualizing High-Dimensional Data

arXiv: https://arxiv.org/abs/2504.08875 · HTML: https://mlsanity.com/paper/2504.08875/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 6 references that are in the map.
- First posted on arXiv 11 Apr 2025.

## Built on by (most cited first, 1 of 1)

- [Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization](https://mlsanity.com/paper/2606.09587/) (2026)

## Abstract (arXiv)

Motivation: The visualization and analysis of high-dimensional data are essential in biomedical research. There is a need for secure, scalable, and reproducible tools to facilitate data exploration and interpretation. Results: We introduce DataMap, a browser-based application for visualization of high-dimensional data using heatmaps, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE). DataMap runs in the web browser, ensuring data privacy while eliminating the need for installation or a server. The application has an intuitive user interface for data transformation, annotation, and generation of reproducible R code. Availability and Implementation: Freely available as a GitHub page https://gexijin.github.io/datamap/. The source code can be found at https://github.com/gexijin/datamap, and can also be installed as an R package. Contact: Xijin.Ge@sdstate.ed