Virtual Data Cosmos -- Information Design in Modern Astronomy

TL;DR

The paper presents Virtual Data Cosmos, a VR-based interactive visualization tool designed to help astronomers explore and understand large, complex X-ray data sets classified by machine learning algorithms, enhancing data exploration.

Contribution

It introduces a novel VR visualization platform for multidimensional astronomical data, improving interpretability and exploration of big data in astronomy.

Findings

Enhanced data exploration through VR interface

Improved understanding of ML classification results

Facilitated discovery of data structures and relationships

Abstract

Where do cosmic X-rays come from? Every new unidentified X-ray source could potentially revolutionize our understanding of the universe. The international collaborative astronomy project EXTraS aimed at automatically classifying new sources of X-ray emission (e.g., stars or galaxies) in the large observation database of the X-ray satellite XMM-Newton. Because data archives have reached dimensions of big data astronomers used different machine-learning (ML) random forest decision tree algorithms that performed the classification process. In this bachelor thesis in information design, I was interested in the challenge to visualize these big data sets and the results of the ML algorithms in an interactive and intuitive way to facilitate the visual exploration of its internal structures and relationships. The VIRTUAL DATA COSMOS is an interactive data visualization tool in virtual reality (VR) for scientists to explore multidimensional data sets.