DocumentCode :
29454
Title :
An Efficient Framework for Generating Storyline Visualizations from Streaming Data
Author :
Tanahashi, Yuzuru ; Chien-Hsin Hsueh ; Kwan-Liu Ma
Author_Institution :
VIDI Res. Group, Univ. California, Davis, CA, USA
Volume :
21
Issue :
6
fYear :
2015
fDate :
June 1 2015
Firstpage :
730
Lastpage :
742
Abstract :
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.
Keywords :
data visualisation; humanities; inference mechanisms; computational efficiency; data management scheme; data streaming; layout computation; layout construction algorithm; layout refinement algorithm; storyline visualization framework; storyline visualization generation; visual clarity; Algorithm design and analysis; Data visualization; Feeds; Layout; Optimization; Social network services; Visualization; Storyline visualization; layout algorithms; streaming data; time-varying data;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2015.2392771
Filename :
7015617
Link To Document :
بازگشت