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

School of Computer, Data & Mathematical Sciences

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

3 Citations (Scopus)

Abstract

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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title = "Visualizing large hierarchies with Drawer Trees",

abstract = "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 - 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 - 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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