English

iTrace : Interactive Tracing of Cross-View Data Relationships

Human-Computer Interaction 2025-05-30 v1

Abstract

Exploring data relations across multiple views has been a common task in many domains such as bioinformatics, cybersecurity, and healthcare. To support this, various techniques (e.g., visual links and brushing and linking) are used to show related visual elements across views via lines and highlights. However, understanding the relations using these techniques, when many related elements are scattered, can be difficult due to spatial distance and complexity. To address this, we present iTrace, an interactive visualization technique to effectively trace cross-view data relationships. iTrace leverages the concept of interactive focus transitions, which allows users to see and directly manipulate their focus as they navigate between views. By directing the user's attention through smooth transitions between related elements, iTrace makes it easier to follow data relationships. We demonstrate the effectiveness of iTrace with a user study, and we conclude with a discussion of how iTrace can be broadly used to enhance data exploration in various types of visualizations.

Keywords

Cite

@article{arxiv.2505.23079,
  title  = {iTrace : Interactive Tracing of Cross-View Data Relationships},
  author = {Abdul Rahman Shaikh and Maoyuan Sun and Xingchen Liu and Hamed Alhoori and Jian Zhao and David Koop},
  journal= {arXiv preprint arXiv:2505.23079},
  year   = {2025}
}

Comments

13 pages, 14 figures, accepted to Graphics Interface 2025

R2 v1 2026-07-01T02:47:46.258Z