TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories

Naoko Sawada; Masanori Nakayama; Hsiang Yun Wu; Makoto Uemura; Issei Fujishiro

doi:10.1145/3095140.3095154

TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories

Naoko Sawada, Masanori Nakayama, Hsiang Yun Wu, Makoto Uemura, Issei Fujishiro

Department of Information and Computer Science

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

3 Citations (Scopus)

Abstract

Astronomers have been observing blazars to solve the mystery of the relativistic jet. A technique called TimeTubes uses a 3D volumetric tube to visualize the time-dependent multivariate observed datasets and allows astronomers to interactively analyze the dynamic behavior of and relationship among those variables. However, the observed datasets themselves exhibit uncertainty due to their errors and missing periods, whereas periods interpolated by TimeTubes result in a different type of uncertainty. In this paper, we present a technique for ameliorating such data-and mappinginherent uncertainties: visual fusion of datasets for the same blazar from two different observatories. Visual data fusion with Time-Tubes enables astronomers to validate the datasets in a meticulous manner.

Original language	English
Title of host publication	CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference
Publisher	Association for Computing Machinery
Volume	Part F128640
ISBN (Electronic)	9781450352284
DOIs	https://doi.org/10.1145/3095140.3095154
Publication status	Published - 2017 Jun 27
Event	2017 Computer Graphics International Conference, CGI 2017 - Yokohama, Japan Duration: 2017 Jun 27 → 2017 Jun 30

Other

Other	2017 Computer Graphics International Conference, CGI 2017
Country/Territory	Japan
City	Yokohama
Period	17/6/27 → 17/6/30

Keywords

Astrophysics
Blazer
Time-varying multivariate visualization
Uncertainty visualization

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

Access to Document

10.1145/3095140.3095154

Cite this

Sawada, N., Nakayama, M., Wu, H. Y., Uemura, M., & Fujishiro, I. (2017). TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories. In CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference (Vol. Part F128640). [a14] Association for Computing Machinery. https://doi.org/10.1145/3095140.3095154

TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories. / Sawada, Naoko; Nakayama, Masanori; Wu, Hsiang Yun et al.
CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference. Vol. Part F128640 Association for Computing Machinery, 2017. a14.

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

Sawada, N, Nakayama, M, Wu, HY, Uemura, M & Fujishiro, I 2017, TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories. in CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference. vol. Part F128640, a14, Association for Computing Machinery, 2017 Computer Graphics International Conference, CGI 2017, Yokohama, Japan, 17/6/27. https://doi.org/10.1145/3095140.3095154

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AU - Fujishiro, Issei

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AB - Astronomers have been observing blazars to solve the mystery of the relativistic jet. A technique called TimeTubes uses a 3D volumetric tube to visualize the time-dependent multivariate observed datasets and allows astronomers to interactively analyze the dynamic behavior of and relationship among those variables. However, the observed datasets themselves exhibit uncertainty due to their errors and missing periods, whereas periods interpolated by TimeTubes result in a different type of uncertainty. In this paper, we present a technique for ameliorating such data-and mappinginherent uncertainties: visual fusion of datasets for the same blazar from two different observatories. Visual data fusion with Time-Tubes enables astronomers to validate the datasets in a meticulous manner.

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TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories

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Keywords

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