Visualizing large hierarchies with Drawer Trees

Yalong Yang; Ning Dou; Shuai Zhao; Zhichao Yang; Kang Zhang; Quang Vinh Nguyen

doi:10.1145/2554850.2554870

Visualizing large hierarchies with Drawer Trees

Yalong Yang, Ning Dou, Shuai Zhao, Zhichao Yang, Kang Zhang, Quang Vinh Nguyen

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

3 Citations (Scopus)

Abstract

![CDATA[Enclosure partitioning approaches, such as Treemaps, have proved their effectiveness in visualizing large hierarchical structures within a compact and limited display area. Most of the Treemaps techniques do not use node-links to show the structural relations. This paper presents a new tree visualization approach known as Drawer-Tree that can be used to present the structure, organization and interrelation of big data. By utilizing the display space with traditional node-link visualization, we have developed a novel method for visualizing tree structures with high scalability. The name “drawer" is a metaphor that helps people understand the visualization.]]

Original language	English
Title of host publication	Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC 2014), Gyeongju, Republic of Korea, 24-28 March 2014
Publisher	Association for Computing Machinery
Pages	951-956
Number of pages	6
ISBN (Print)	9781450324694
DOIs	https://doi.org/10.1145/2554850.2554870
Publication status	Published - 2014
Event	Symposium on Applied Computing - Duration: 24 Mar 2014 → …

Conference

Conference	Symposium on Applied Computing
Period	24/03/14 → …

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10.1145/2554850.2554870

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@inproceedings{0babc0788a00423599cc56e8b38f049b,

title = "Visualizing large hierarchies with Drawer Trees",

abstract = "![CDATA[Enclosure partitioning approaches, such as Treemaps, have proved their effectiveness in visualizing large hierarchical structures within a compact and limited display area. Most of the Treemaps techniques do not use node-links to show the structural relations. This paper presents a new tree visualization approach known as Drawer-Tree that can be used to present the structure, organization and interrelation of big data. By utilizing the display space with traditional node-link visualization, we have developed a novel method for visualizing tree structures with high scalability. The name “drawer{"} is a metaphor that helps people understand the visualization.]]",

author = "Yalong Yang and Ning Dou and Shuai Zhao and Zhichao Yang and Kang Zhang and Nguyen, {Quang Vinh}",

year = "2014",

doi = "10.1145/2554850.2554870",

language = "English",

isbn = "9781450324694",

pages = "951--956",

booktitle = "Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC 2014), Gyeongju, Republic of Korea, 24-28 March 2014",

publisher = "Association for Computing Machinery",

note = "Symposium on Applied Computing ; Conference date: 24-03-2014",

}

Yang, Y, Dou, N, Zhao, S, Yang, Z, Zhang, K & Nguyen, QV 2014, Visualizing large hierarchies with Drawer Trees. in Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC 2014), Gyeongju, Republic of Korea, 24-28 March 2014. Association for Computing Machinery, pp. 951-956, Symposium on Applied Computing, 24/03/14. https://doi.org/10.1145/2554850.2554870

TY - GEN

T1 - Visualizing large hierarchies with Drawer Trees

AU - Yang, Yalong

AU - Dou, Ning

AU - Zhao, Shuai

AU - Yang, Zhichao

AU - Zhang, Kang

AU - Nguyen, Quang Vinh

PY - 2014

Y1 - 2014

N2 - ![CDATA[Enclosure partitioning approaches, such as Treemaps, have proved their effectiveness in visualizing large hierarchical structures within a compact and limited display area. Most of the Treemaps techniques do not use node-links to show the structural relations. This paper presents a new tree visualization approach known as Drawer-Tree that can be used to present the structure, organization and interrelation of big data. By utilizing the display space with traditional node-link visualization, we have developed a novel method for visualizing tree structures with high scalability. The name “drawer" is a metaphor that helps people understand the visualization.]]

AB - ![CDATA[Enclosure partitioning approaches, such as Treemaps, have proved their effectiveness in visualizing large hierarchical structures within a compact and limited display area. Most of the Treemaps techniques do not use node-links to show the structural relations. This paper presents a new tree visualization approach known as Drawer-Tree that can be used to present the structure, organization and interrelation of big data. By utilizing the display space with traditional node-link visualization, we have developed a novel method for visualizing tree structures with high scalability. The name “drawer" is a metaphor that helps people understand the visualization.]]

UR - http://handle.uws.edu.au:8081/1959.7/554101

UR - http://www.acm.org/conferences/sac/sac2014/

U2 - 10.1145/2554850.2554870

DO - 10.1145/2554850.2554870

M3 - Conference Paper

SN - 9781450324694

SP - 951

EP - 956

BT - Proceedings of the 29th Annual ACM Symposium on Applied Computing (SAC 2014), Gyeongju, Republic of Korea, 24-28 March 2014

PB - Association for Computing Machinery

T2 - Symposium on Applied Computing

Y2 - 24 March 2014

ER -

Visualizing large hierarchies with Drawer Trees

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