1.5D Egocentric Dynamic Network Visualization

Dynamic network visualization has been a challenging research topic due to the visual and computational complexity introduced by the extra time dimension. Existing solutions are usually good for overview and presentation tasks, but not for the interactive analysis of a large dynamic network. We intr...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 21(2015), 5 vom: 10. Mai, Seite 624-37
1. Verfasser: Shi, Lei (VerfasserIn)
Weitere Verfasser: Wang, Chen, Wen, Zhen, Qu, Huamin, Lin, Chuang, Liao, Qi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2015
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article
LEADER 01000naa a22002652 4500
001 NLM252629507
003 DE-627
005 20231224164520.0
007 cr uuu---uuuuu
008 231224s2015 xx |||||o 00| ||eng c
024 7 |a 10.1109/TVCG.2014.2383380  |2 doi 
028 5 2 |a pubmed24n0842.xml 
035 |a (DE-627)NLM252629507 
035 |a (NLM)26357209 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Shi, Lei  |e verfasserin  |4 aut 
245 1 0 |a 1.5D Egocentric Dynamic Network Visualization 
264 1 |c 2015 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 01.12.2015 
500 |a Date Revised 11.09.2015 
500 |a published: Print 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a Dynamic network visualization has been a challenging research topic due to the visual and computational complexity introduced by the extra time dimension. Existing solutions are usually good for overview and presentation tasks, but not for the interactive analysis of a large dynamic network. We introduce in this paper a new approach which considers only the dynamic network central to a focus node, also known as the egocentric dynamic network. Our major contribution is a novel 1.5D visualization design which greatly reduces the visual complexity of the dynamic network without sacrificing the topological and temporal context central to the focus node. In our design, the egocentric dynamic network is presented in a single static view, supporting rich analysis through user interactions on both time and network. We propose a general framework for the 1.5D visualization approach, including the data processing pipeline, the visualization algorithm design, and customized interaction methods. Finally, we demonstrate the effectiveness of our approach on egocentric dynamic network analysis tasks, through case studies and a controlled user experiment comparing with three baseline dynamic network visualization methods 
650 4 |a Journal Article 
700 1 |a Wang, Chen  |e verfasserin  |4 aut 
700 1 |a Wen, Zhen  |e verfasserin  |4 aut 
700 1 |a Qu, Huamin  |e verfasserin  |4 aut 
700 1 |a Lin, Chuang  |e verfasserin  |4 aut 
700 1 |a Liao, Qi  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on visualization and computer graphics  |d 1996  |g 21(2015), 5 vom: 10. Mai, Seite 624-37  |w (DE-627)NLM098269445  |x 1941-0506  |7 nnns 
773 1 8 |g volume:21  |g year:2015  |g number:5  |g day:10  |g month:05  |g pages:624-37 
856 4 0 |u http://dx.doi.org/10.1109/TVCG.2014.2383380  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 21  |j 2015  |e 5  |b 10  |c 05  |h 624-37