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.
Original language | English (US) |
---|---|
Article number | 7015617 |
Pages (from-to) | 730-742 |
Number of pages | 13 |
Journal | IEEE Transactions on Visualization and Computer Graphics |
Volume | 21 |
Issue number | 6 |
DOIs | |
State | Published - Jun 1 2015 |
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Keywords
- layout algorithms
- Storyline visualization
- streaming data
- time-varying data
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design
Cite this
An efficient framework for generating storyline visualizations from streaming data. / Tanahashi, Yuzuru; Hsueh, Chien Hsin; Ma, Kwan-Liu.
In: IEEE Transactions on Visualization and Computer Graphics, Vol. 21, No. 6, 7015617, 01.06.2015, p. 730-742.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An efficient framework for generating storyline visualizations from streaming data
AU - Tanahashi, Yuzuru
AU - Hsueh, Chien Hsin
AU - Ma, Kwan-Liu
PY - 2015/6/1
Y1 - 2015/6/1
N2 - 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.
AB - 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.
KW - layout algorithms
KW - Storyline visualization
KW - streaming data
KW - time-varying data
UR - http://www.scopus.com/inward/record.url?scp=84929164545&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84929164545&partnerID=8YFLogxK
U2 - 10.1109/TVCG.2015.2392771
DO - 10.1109/TVCG.2015.2392771
M3 - Article
AN - SCOPUS:84929164545
VL - 21
SP - 730
EP - 742
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
SN - 1077-2626
IS - 6
M1 - 7015617
ER -