TY - JOUR
T1 - TimeTubesX
T2 - A Query-Driven Visual Exploration of Observable, Photometric, and Polarimetric Behaviors of Blazars
AU - Sawada, Naoko
AU - Uemura, Makoto
AU - Beyer, Johanna
AU - Pfister, Hanspeter
AU - Fujishiro, Issei
N1 - Funding Information:
The present work has been financially supported in part by a MEXT KAKENHI Grant-in-Aid for Scientific Research(A) No. 17H00737 and King Abdullah University of Science and Technology (KAUST) and the KAUSTOffice of Sponsored Research (OSR)'s Award, OSR-2015-CCF-2533-0.
Publisher Copyright:
© 1995-2012 IEEE.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - Blazars are celestial bodies of high interest to astronomers. In particular, through the analysis of photometric and polarimetric observations of blazars, astronomers aim to understand the physics of the blazar's relativistic jet. However, it is challenging to recognize correlations and time variations of the observed polarization, intensity, and color of the emitted light. In our prior study, we proposed TimeTubes to visualize a blazar dataset as a 3D volumetric tube. In this paper, we build primarily on the TimeTubes representation of blazar datasets to present a new visual analytics environment named TimeTubesX, into which we have integrated sophisticated feature and pattern detection techniques for effective location of observable and recurring time variation patterns in long-term, multi-dimensional datasets. Automatic feature extraction detects time intervals corresponding to well-known blazar behaviors. Dynamic visual querying allows users to search long-term observations for time intervals similar to a time interval of interest (query-by-example) or a sketch of temporal patterns (query-by-sketch). Users are also allowed to build up another visual query guided by the time interval of interest found in the previous process and refine the results. We demonstrate how TimeTubesX has been used successfully by domain experts for the detailed analysis of blazar datasets and report on the results.
AB - Blazars are celestial bodies of high interest to astronomers. In particular, through the analysis of photometric and polarimetric observations of blazars, astronomers aim to understand the physics of the blazar's relativistic jet. However, it is challenging to recognize correlations and time variations of the observed polarization, intensity, and color of the emitted light. In our prior study, we proposed TimeTubes to visualize a blazar dataset as a 3D volumetric tube. In this paper, we build primarily on the TimeTubes representation of blazar datasets to present a new visual analytics environment named TimeTubesX, into which we have integrated sophisticated feature and pattern detection techniques for effective location of observable and recurring time variation patterns in long-term, multi-dimensional datasets. Automatic feature extraction detects time intervals corresponding to well-known blazar behaviors. Dynamic visual querying allows users to search long-term observations for time intervals similar to a time interval of interest (query-by-example) or a sketch of temporal patterns (query-by-sketch). Users are also allowed to build up another visual query guided by the time interval of interest found in the previous process and refine the results. We demonstrate how TimeTubesX has been used successfully by domain experts for the detailed analysis of blazar datasets and report on the results.
KW - Visual analytics
KW - astrophysics
KW - blazar
KW - feature extraction
KW - multi-dimensional
KW - time-dependent visualization
KW - visual query
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U2 - 10.1109/TVCG.2020.3025090
DO - 10.1109/TVCG.2020.3025090
M3 - Article
C2 - 32946396
AN - SCOPUS:85125550349
SN - 1077-2626
VL - 28
SP - 1917
EP - 1929
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 4
ER -