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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.23079 |
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| _version_ | 1866918037673738240 |
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| author | Shaikh, Abdul Rahman Sun, Maoyuan Liu, Xingchen Alhoori, Hamed Zhao, Jian Koop, David |
| author_facet | Shaikh, Abdul Rahman Sun, Maoyuan Liu, Xingchen Alhoori, Hamed Zhao, Jian Koop, David |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_23079 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | iTrace : Interactive Tracing of Cross-View Data Relationships Shaikh, Abdul Rahman Sun, Maoyuan Liu, Xingchen Alhoori, Hamed Zhao, Jian Koop, David Human-Computer Interaction 68U05 H.5.2; I.3.6; I.3.8 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. |
| title | iTrace : Interactive Tracing of Cross-View Data Relationships |
| topic | Human-Computer Interaction 68U05 H.5.2; I.3.6; I.3.8 |
| url | https://arxiv.org/abs/2505.23079 |