Effectiveness of Feature-Driven Storytelling in 3D Time-Varying Data Visualization

2017 ◽  
Vol 2017 (1) ◽  
pp. 99-109
Author(s):  
Li Yu ◽  
Lane Harrison ◽  
Aidong Lu
Author(s):  
Satsuki Kumatani ◽  
Takayuki Itoh ◽  
Yousuke Motohashi ◽  
Keisuke Umezu ◽  
Masahiro Takatsuka

Author(s):  
Trefor Williams ◽  
James Abello ◽  
John Betak ◽  
David Desimone

The Federal Railroad Administration grade crossing accident database contains numerous interrelated variables. Understanding of how the variables are interrelated can be enhanced using modern visualization techniques. These techniques can allow managers from railroads and government agencies to find complex variables relationships not usually provided by routine statistical analyses. For this research we have developed several dashboards of linked visualizations using the Weave data visualization software [5]. Our visualizations explore various accident types of concern to the railroad industry including trespassing and pedestrian accidents, passenger train accidents, actions of highway users involved in accidents, and the effect of different types of warning devices on grade crossing accidents. In addition, we are currently developing an advanced visualization system that views the accident data as time varying events occurring over a fixed grade crossings topology. This view allows the application of a recent network data abstraction termed “Graph Cards.” We present initial examples of the advanced system that provides a variety of filtering mechanisms to view statistical distributions and their time varying behavior over the grade crossings topology.


2010 ◽  
Vol 29 (7) ◽  
pp. 2271-2280 ◽  
Author(s):  
Li Yu ◽  
Aidong Lu ◽  
William Ribarsky ◽  
Wei Chen

2015 ◽  
Vol 21 (12) ◽  
pp. 1415-1426 ◽  
Author(s):  
Ming-Te Chi ◽  
Shih-Syun Lin ◽  
Shiang-Yi Chen ◽  
Chao-Hung Lin ◽  
Tong-Yee Lee

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