Brushing Feature Values in Immersive Graph Visualization Environment

TL;DR

This paper introduces an immersive analytics system for exploring multidimensional node features in large graphs, enabling interactive visualization through label-axes and brushing operations to facilitate data analysis.

Contribution

The paper presents a novel immersive visualization system specifically designed for multidimensional graph node features, enhancing interactive exploration capabilities.

Findings

Effective visualization of multidimensional features on large graphs.

Interactive brushing controls for detailed data exploration.

Application to Twitter user data demonstrates system utility.

Abstract

There are a variety of graphs where multidimensional feature values are assigned to the nodes. Visualization of such datasets is not an easy task since they are complex and often huge. Immersive Analytics is a powerful approach to support the interactive exploration of such large and complex data. Many recent studies on graph visualization have applied immersive analytics frameworks. However, there have been few studies on immersive analytics for visualization of multidimensional attributes associated with the input graphs. This paper presents a new immersive analytics system that supports the interactive exploration of multidimensional feature values assigned to the nodes of input graphs. The presented system displays label-axes corresponding to the dimensions of feature values, and label-edges that connect label-axes and corresponding to the nodes. The system supports brushing operations which controls the display of edges that connect a label-axis and nodes of the graph. This paper introduces visualization examples with a graph dataset of Twitter users and reviews by experts on graph data analysis.