TY - GEN
T1 - TimeSpiral, an enhanced interactive visual system for time series data
AU - Zhang, Di
AU - Zhu, Ligu
AU - Wang, Chengcheng
AU - Zhang, Lei
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/5/23
Y1 - 2016/5/23
N2 - Time dimension has always been an important measurement scale of human society, producing large amounts of time-series data all the time in the fields of science, engineering, economics and so on. Exploring correlation features and periodic trends of multi-dimensional time-series data is the emphasis in the research of visual analytics. A visual interactive system named TimeSprial is proposed on the basis of past cases and visualization methods in this paper. The system is designed based on the concepts of time granularity and time primitive, so as to explore correlation features and periodic trends of data dimensions through visual analysis. TimeSprial integrates various visualization layout methods of periodic data, such as ring diagram and curve graph, assisted by a variety of interactive models. Finally, case analysis of actual data sets shows the effectiveness of our approach in the exploration and understanding of multi-dimensional time-series data.
AB - Time dimension has always been an important measurement scale of human society, producing large amounts of time-series data all the time in the fields of science, engineering, economics and so on. Exploring correlation features and periodic trends of multi-dimensional time-series data is the emphasis in the research of visual analytics. A visual interactive system named TimeSprial is proposed on the basis of past cases and visualization methods in this paper. The system is designed based on the concepts of time granularity and time primitive, so as to explore correlation features and periodic trends of data dimensions through visual analysis. TimeSprial integrates various visualization layout methods of periodic data, such as ring diagram and curve graph, assisted by a variety of interactive models. Finally, case analysis of actual data sets shows the effectiveness of our approach in the exploration and understanding of multi-dimensional time-series data.
KW - human-computer interaction
KW - periodic trends
KW - time-series data
KW - user interface
KW - visual analysis
UR - http://www.scopus.com/inward/record.url?scp=84978062907&partnerID=8YFLogxK
U2 - 10.1109/INFOMAN.2016.7477546
DO - 10.1109/INFOMAN.2016.7477546
M3 - Conference Proceeding
AN - SCOPUS:84978062907
T3 - Proceedings of 2016 International Conference on Information Management, ICIM 2016
SP - 127
EP - 133
BT - Proceedings of 2016 International Conference on Information Management, ICIM 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Conference on Information Management, ICIM 2016
Y2 - 7 May 2016 through 8 May 2016
ER -