XR and Hybrid Data Visualization Spaces for Enhanced Data Analytics

TL;DR

This paper explores how integrating 2D and 3D visualizations within XR environments can improve data analytics by making complex, high-dimensional data more understandable and accessible.

Contribution

It introduces a framework for combining traditional and XR-based visualizations and demonstrates its effectiveness through three case studies.

Findings

XR enhances understanding of high-dimensional data.

Integrated visualizations improve data analysis efficiency.

Case studies show practical benefits of XR in data analytics.

Abstract

The growing complexity and information content of data, together with the need to understand both the complex structures, relationships, and phenomena present in these data spaces, compounded with the emerging need to understand the results produced by AI tools used to analyze the data, requires development of novel, effective data visualization tools. Much of the growing complexity is reflected in the increasing dimensionality of data spaces, where extended reality (XR) naturally emerges as a candidate to help extend our capability for higher dimensional understanding. However, humans often understand lower dimensionality representations more effectively. Still, XR offers an opportunity for a seamless integration of simulated traditional data displays within the 3-dimensional virtual data spaces, leading to more intuitive and more effective data analytics. In this paper we present an overview of the benefits of seamlessly integrated 2-dimensional and 3-dimensional interactive visual representations embedded in XR spaces, and present three case studies that leverage these approaches for more efficient data analytics.