Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data

Christopher Koehler; Andrew Berger; Raksha Rajashekar; Thomas Wischgoll; Simon Su

doi:10.1109/BigData47090.2019.9006500

Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data

Christopher Koehler, Andrew Berger, Raksha Rajashekar, Thomas Wischgoll, Simon Su

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

© 2019 IEEE. There is no one display device or software package that is ideally suited for interactively visualizing related nonspatial, 1D, 2D, 3D, and 4D datasets. This is a major drawback, as the benefits of interactive visualization and advanced display technologies cannot be brought to bear. The Dynamic Collaborative Visualization Ecosystem (DynaCoVE) framework addresses this limitation by unifying SciVis, InfoVis, and display technology tools. Pre-existing packages are wrapped as DynaCoVE clients. This entails tracking user interactions with their GUI's and also automatically updating them in response to cues from the DynaCoVE server. The DynaCoVE server then acts as a message broker between many collaborating clients. A messaging protocol was defined based on ZeroMQ's majordomo protocol to enable efficient communication between clients and the server. Thus, visualization software packages that were never intended to be used together can be linked to perform cross display visual analytics. The system is intended to be data and user centric while remaining software, algorithm and display agnostic. This is accomplished in part by providing a common metavisualization graph interface to setup cross-display visualizations. To date DynaCoVE clients for Looker, VisIt, and VTK have been tested together with traditional monitors, tiled displays, and an immersive CAVE-type system.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
Editors	Chaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
Publisher	IEEE
Pages	3968-3977
Number of pages	10
ISBN (Electronic)	9781728108582
DOIs	https://doi.org/10.1109/BigData47090.2019.9006500
State	Published - Dec 2019
Event	2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States Duration: Dec 9 2019 → Dec 12 2019

Conference

Conference	2019 IEEE International Conference on Big Data, Big Data 2019
Country/Territory	United States
City	Los Angeles
Period	12/9/19 → 12/12/19

ASJC Scopus Subject Areas

Artificial Intelligence
Computer Networks and Communications
Information Systems
Information Systems and Management

Keywords

Data fusion and integration
collaborative and distributed visualization
coordinated and multiple views
integrating spatial and non-spatial data visualization
large and high-res displays

Disciplines

Computer Sciences
Engineering

Access to Document

10.1109/BigData47090.2019.9006500License: Unspecified

Cite this

Koehler, C., Berger, A., Rajashekar, R., Wischgoll, T., & Su, S. (2019). Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 3968-3977). Article 9006500 IEEE. https://doi.org/10.1109/BigData47090.2019.9006500

Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data. / Koehler, Christopher; Berger, Andrew; Rajashekar, Raksha et al.
Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. ed. / Chaitanya Baru; Jun Huan; Latifur Khan; Xiaohua Tony Hu; Ronay Ak; Yuanyuan Tian; Roger Barga; Carlo Zaniolo; Kisung Lee; Yanfang Fanny Ye. IEEE, 2019. p. 3968-3977 9006500.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Koehler, C, Berger, A, Rajashekar, R, Wischgoll, T & Su, S 2019, Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data. in C Baru, J Huan, L Khan, XT Hu, R Ak, Y Tian, R Barga, C Zaniolo, K Lee & YF Ye (eds), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019., 9006500, IEEE, pp. 3968-3977, 2019 IEEE International Conference on Big Data, Big Data 2019, Los Angeles, United States, 12/9/19. https://doi.org/10.1109/BigData47090.2019.9006500

Koehler C, Berger A, Rajashekar R, Wischgoll T, Su S. Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data. In Baru C, Huan J, Khan L, Hu XT, Ak R, Tian Y, Barga R, Zaniolo C, Lee K, Ye YF, editors, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. IEEE. 2019. p. 3968-3977. 9006500 doi: 10.1109/BigData47090.2019.9006500

Koehler, Christopher ; Berger, Andrew ; Rajashekar, Raksha et al. / Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data. Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. editor / Chaitanya Baru ; Jun Huan ; Latifur Khan ; Xiaohua Tony Hu ; Ronay Ak ; Yuanyuan Tian ; Roger Barga ; Carlo Zaniolo ; Kisung Lee ; Yanfang Fanny Ye. IEEE, 2019. pp. 3968-3977

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ER -

Dynamic Collaborative Visualization Ecosystem to Support the Analysis of Large-Scale Disparate Data

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

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Cite this