Issue No. 06 - June (2015 vol. 21)
Yuzuru Tanahashi , VIDI Research Group, University California, Davis, CA
Chien-Hsin Hsueh , VIDI Research Group, University California, Davis, CA
Kwan-Liu Ma , VIDI Research Group, University California, Davis, CA
This paper presents a novel framework for applying storyline visualizations to streaming data. The framework includes three components: a new data management scheme for processing and storing the incoming data, a layout construction algorithm specifically designed for incrementally generating storylines from streaming data, and a layout refinement algorithm for improving the legibility of the visualization. By dividing the layout computation to two separate components, one for constructing and another for refining, our framework effectively provides the users with the ability to follow and reason dynamic data. The evaluation studies of our storyline visualization framework demonstrate its efficacy to present streaming data as well as its superior performance over existing methods in terms of both computational efficiency and visual clarity.
data visualisation, humanities, inference mechanisms
Y. Tanahashi, C. Hsueh and K. Ma, "An Efficient Framework for Generating Storyline Visualizations from Streaming Data," in IEEE Transactions on Visualization & Computer Graphics, vol. 21, no. 6, pp. 730-742, 2015.