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