TY - GEN
T1 - TimeTubes
T2 - 2018 IEEE Scientific Visualization Conference, SciVis 2018
AU - Sawada, Naoko
AU - Nakayama, Masanori
AU - Uemura, Makoto
AU - Fujishiro, Issei
N1 - Funding Information:
The present work has been financially supported in part by MEXT KAKENHI Grants-in-Aid for Scientific Research on Innovative Areas No. 25120014 and No. 25120007 and Microsoft Research Asia Collaborative Research Program 2018.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/10
Y1 - 2018/10
N2 - Blazars are attractive objects for astronomers to observe in order to demystify the relativistic jet. Astronomers need to classify characteristic temporal variation patterns and correlations of multidimensional time-dependent observed blazar datasets. Our visualization scheme, called TimeTubes, allows them to easily explore and analyze such datasets geometrically as a 3D volumetric tube. Even with TimeTubes, however, data analysis over such long-term datasets costs them so much labor and may cause a biased analysis. This paper, therefore, attempts to incorporate into the current prototype of TimeTubes, a new functionality: feature extraction, which supports astronomers' efficient data analysis by automatically extracting characteristic spatiotemporal subspaces.
AB - Blazars are attractive objects for astronomers to observe in order to demystify the relativistic jet. Astronomers need to classify characteristic temporal variation patterns and correlations of multidimensional time-dependent observed blazar datasets. Our visualization scheme, called TimeTubes, allows them to easily explore and analyze such datasets geometrically as a 3D volumetric tube. Even with TimeTubes, however, data analysis over such long-term datasets costs them so much labor and may cause a biased analysis. This paper, therefore, attempts to incorporate into the current prototype of TimeTubes, a new functionality: feature extraction, which supports astronomers' efficient data analysis by automatically extracting characteristic spatiotemporal subspaces.
KW - Empirical studies in visualization
KW - Human-centered computing
KW - Scientific visualization
KW - Visualization
KW - Visualization application domains
UR - http://www.scopus.com/inward/record.url?scp=85072951292&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072951292&partnerID=8YFLogxK
U2 - 10.1109/SciVis.2018.8823802
DO - 10.1109/SciVis.2018.8823802
M3 - Conference contribution
AN - SCOPUS:85072951292
T3 - 2018 IEEE Scientific Visualization Conference, SciVis 2018 - Proceedings
SP - 67
EP - 71
BT - 2018 IEEE Scientific Visualization Conference, SciVis 2018 - Proceedings
A2 - Geveci, Berk
A2 - Kindlmann, Gordon
A2 - Nonato, Luis Gustavo
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 October 2018 through 26 October 2018
ER -