Summary

TimeTubesX is a system for efficient and detailed visual analysis of multi-dimensional time-dependent observed datasets of BLAZARs. Blazars are in a class of extremely luminous galactic nuclei, which are called active galactic nuclei (AGN). They eject a relativistic jet from their central black hole towards the Earth, as illustrated in the following figure. Astronomers observe them to demystify the intricate physics of these jets’ structures and activities of the internal magnetic field. Hiroshima Astrophysical Science Center, with which we collaborate, observes the polarization (A of the following figure), intensity (B), and color (C) of the emitted light.

Observation of a blazar and visual encoding for blazar data

Astronomers analyze time variations and correlations of those observed properties to identify the spatiotemporal features of blazars. As illustrated in (D) of the above figure, TimeTubes visualizes a single blazar dataset as a 3D volumetric tube to allow users to intuitively recognize and interactively analyze time variations and correlations in multi-dimensional time-dependent datasets. In TimeTubes, users are allowed to compare and fuse multiple datasets for the same/different blazar(s), which is termed the visual data fusion. The visual data fusion ameliorates uncertainties caused by missing data and observation errors. Please refer to our paper [A-1] for the detailed information about the 3D visualization of TimeTubes, its interactions, the visual data fusion, etc. 

Main visualization panel of TimeTubesX

TimeTubesX is a browser-based application for blazar observed datasets, which is an extended version of TimeTubes. TimeTubesX provides automatic feature extraction methods for characteristic blazar behaviors [IC-1] and dynamic visual querying functions that locate time intervals similar to a specific region of interest or user-drawn sketch. TimeTubesX is effective for the discovery of characteristic blazar behaviors, relatively short time variations, and recurring time variation patterns.

TimeTubesX is an open-sourced software. You can play around TimeTubesX with our demo data.

GitHub

Members

The members with a gray background do not involve in the project now. The icon is put beside the name of the members who belong to Fujishiro Laboratory now.

NameAffiliationWeb site
Naoko SawadaKeio UniversityPersonal website
Makoto UemuraHiroshima UniversityPersonal website
Hanspter PfisterHarvard UniversityHarvard Visual Computing Group
Johanna BeyerHarvard UniversityPersonal website
Longyin Xu2014-2016
Masanori NakayamaKeio University
Hsiang-Yun Wu TU WienPersonal website

Video

Publications

Underlined authors belong/belonged to Fujishiro Laboratory.

Journals

  1. Naoko Sawada, Makoto Uemura, Johanna Beyer, Hanspeter Pfister, Issei Fujishiro: “ TimeTubesX: A query-driven visual exploration of observable, photometric, and polarimetric behaviors of blazars,” IEEE Transactions on Visualization and Computer Graphics, September 18, 2020 (to appear) [doi: 10.1109/TVCG.2020.3025090].
  2. Issei Fujishiro, Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Kazuho Watanabe, Shigeo Takahashi, Makoto Uemura: “TimeTubes: Visual exploration of observed blazar datasets,”Journal of Physics: Conference Series, Vol.1036, No.1, pp.012011:1―012011:13, June 27, 2018 [doi: 10.1088/1742-6596/1036/1/012011].
  3. Makoto Uemura, Ryosuke Itoh, Ioannis Liodakis, Dmitry Blinov, Masanori Nakayama, Naoko Sawada, Hsiang-Yun Wu, Issei Fujishiro: “Optical polarization variations in the blazar PKS1749+096,” Publications of the Astronomical Society of Japan, Vol. 69, No. 6, pp. 96:1–96:12, December 1, 2017 [doi: 10.1093/pasj/psx111].
  4. Makoto Uemura, Rhosuke Itoh, Longyin Xu, Masanori Nakayama, Hsiang-Yun Wu, Kazuho Watanabe, Shigeo Takahashi, Issei Fujishiro: ‘’TimeTubes: Visualization of polarization variations in blazars,” Galaxies, Vol. 4, No. 3, Article No.23, September 3, 2016 [doi: 10.3390/galaxies4030023].

Conferences

International conferences/symposiums

  1. Makoto Uemura, Issei Fujishiro, Naoko Sawada, et al.: “Finding features in erratic polarization variations of blazars,” in Proceedings of International Astronomical Union Symposium 360 Astronomical Polarimetry 2020, Hiroshima, March 2021.Conference page
  2. Naoko Sawada, Masanori Nakayama, Makoto Uemura, Issei Fujishiro: “TimeTubes: Automatic extraction of observable blazar features from long-term, multi-dimensional datasets,” in Proceedings of IEEE VIS 2018, SciVis short paper track, pp. 67―71, Berlin, Germany, October 2126, 2018 [doi: 10.1109/SciVis.2018.8823802].
  3. Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura, Issei Fujishiro: “TimeTubes: Visual fusion for detailed and precise analysis of time-varying multi-dimensional datasets,” in Proceedings of the International Meeting on “High-Dimensional Data-Driven Science” (HD3–2017), Poster, Kyoto, Japan, September 10-13, 2017. Conference page
  4. Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura, Issei Fujishiro: “TimeTubes: Visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories,” in Proceedings of the Computer Graphics International Conference, Short paper, Article No. 14, pp. 16, Keio University Hiyoshi Campus, Kanagawa, Japan, June 2730, 2017 [doi: 10.1145/3095140.3095154].
  5. Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura, Issei Fujishiro: “TimeTubes: Visual fusion for ameliorating uncertainty of blazar datasets from different observatories,” in Proceedings of IEEE PacificVis 2017, Poster, pp.336337, Seoul, Korea, April 1821, 2017.
  6. Longyin Xu, Masanori Nakayama, Hsiang-Yun Wu, Kazuho Watanabe, Shigeo Takahashi, Makoto Uemura, Issei Fujishiro: “TimeTubes: Design of a visualization tool for time-dependent, multi-variate blazar datasets,” in Proceedings of NICOGRAPH International 2016, pp.1521, Hangzhou, China, July 68, 2016 [doi: 10.1109/NicoInt.2016.3].
  7. Makoto Uemura, Longyin Xu, Masanori Nakayama, Hsiang-Yun Wu, Kazuho Watanabe, Shigeo Takahashi, Issei Fujishiro:”TimeTubes: Visualization of polarization variations in blazars,” in Proceedings of Blazars through Sharp Multi-Wavelength Eyes, , May 30―June 3, Málaga, Spain.
  8. Longyin Xu, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura, Issei Fujishiro: “TimeTubes: Preliminary design of visualization tool for time-dependent, multi-variate blazar datasets,” in Proceedings of the International Meeting on “High-Dimensional Data-Driven Science” (HD3–2015), Poster, December 1417, 2015, Kyoto, Japan. Conference page

Domestic conferences/symposiums

  1. Naoko Sawada, Makoto Uemura, Johanna Beyer, Hanspeter Pfister, Issei Fujishiro: “TimeTubesX: A query-driven visual exploration of observable, photometric, and polarimetric behaviors of blazars,” invited talk, in Proceedings of the Visual Computing 2020, pp: 14:1―14:2, Online, December 2―4, 2020 (in Japanese).
  2. Naoko Sawada, Makoto Uemura, Issei Fujishiro: “TimeTubesX: Identifying Characteristic Blazar Behaviors Through Query-Driven Visual Exploration,” in Proceedings of the 48th Symposium on Visualization in Japan, Article No. 088, Online, September 24―26, 2020 (in Japanese).
  3. Naoko Sawada, Masanori Nakayama, Makoto Uemura, Issei Fujishiro: “TimeTubes: Feature extraction of observed blazar datasets for detailed and efficient data analysis,” in Proceedings of the 284th Reports of the Technical Conference of The Institute of Image Electronics Engineers of Japan, pp. 19―23, Hiroshima, Japan, March 1―2, 2018 (in Japanese).
  4. Issei Fujishiro, Shigeo Takahashi, Kazuho Watanabe, Hsiang-Yun Wu, Makoto Uemura. “Consolidation of visualization platform toward facilitating sparse modeling,” in Proceedings of the 5th Public Symposium of KAKENHI Grant-in-Aid for Scientific Research on Innovative Areas “Initiative for High-Dimensional Data-driven Science through Deepening of Sparse Modeling”, Poster, Tokyo, Japan, December 1820, 2017.
  5. Issei Fujishiro, Shigeo Takahashi, Kazuho Watanabe, Hsiang-Yun WuNaoko Sawada, Makoto Uemura: “On the perspicuity of multidimensional data visualization,” in Proceedings of the 1st Public Symposium in the 2017 business year of KAKENHI Grant-in-Aid for Scientific Research on Innovative Areas “Initiative for High-Dimensional Data-driven Science through Deepening of Sparse Modeling”, Poster, Tokyo, Japan, June 5―7, 2017 (in Japanese).
  6. Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura, Issei Fujishiro: “TimeTubes: Visual fusion for ameliorating uncertainty of blazar datasets from different observatories,” in Proceedings of the 79th IPSJ National Convention, Article No. 3X–08, pp. 85―86, Nagoya, Japan, March 16―18, 2017 (in Japanese). Student Encouragement Award [Digital Library]

Others

  1. Naoko Sawada, “Clustering-driven visual analytics for universalities in multi-dimensional time-dependent datasets” invited talk at 5th China-Japan Joint Visualization, Keio University (online), April 14, 2022. Workshop Page
  2. Issei Fujishiro, Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Kazuho Watanabe, Shigeo Takahashi, Makoto Uemura: “TimeTubes: Visual exploration of observed blazar datasets,” two figures selected as the cover images for the printed version of Journal of Physics: Conference Series (Proceedings of International Meeting on High-Dimensional Data-Driven Science (HD3–2017), Vol. 1036, 2018.

Grants

  1. Grant-in-Aid for Scientific Research (A): 17H00737 (2017―2020)
  2. Grant-in-Aid for Scientific Research on Innovative Areas: 25120014(2013―2017)

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