TY - JOUR
T1 - Event-Based Dynamic Graph Visualisation
AU - Simonetto, Paolo
AU - Archambault, Daniel
AU - Kobourov, Stephen
N1 - Funding Information:
We would like to thank Peter Eades for suggesting Event-Based Graph Drawing as a more accurate name for this research at GD 2017. We would also like to thank Derek Greene and Karen Wade for providing the Rugby and Pride & Prejudice data sets. We would like to thank Karen Wade for her insights into the Pride & Prejudice network. This work was supported by EPSRC First Grant EP/N005724/1 and NSF grants CCF-1712119, CCF-1740858, DMS-1839274.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Dynamic graph drawing algorithms take as input a series of timeslices that standard, force-directed algorithms can exploit to compute a layout. However, often dynamic graphs are expressed as a series of events where the nodes and edges have real coordinates along the time dimension that are not confined to discrete timeslices. Current techniques for dynamic graph drawing impose a set of timeslices on this event-based data in order to draw the dynamic graph, but it is unclear how many timeslices should be selected: too many timeslices slows the computation of the layout, while too few timeslices obscures important temporal features, such as causality. To address these limitations, we introduce a novel model for drawing event-based dynamic graphs and the first dynamic graph drawing algorithm, DynNoSlice, that is capable of drawing dynamic graphs in this model. DynNoSlice is an offline, force-directed algorithm that draws event-based, dynamic graphs in the space-time cube (2D+time). We also present a method to extract representative small multiples from the space-time cube. To demonstrate the advantages of our approach, DynNoSlice is compared with state-of-the-art timeslicing methods using a metrics-based experiment. Finally, we present case studies of event-based dynamic data visualised with the new model and algorithm.
AB - Dynamic graph drawing algorithms take as input a series of timeslices that standard, force-directed algorithms can exploit to compute a layout. However, often dynamic graphs are expressed as a series of events where the nodes and edges have real coordinates along the time dimension that are not confined to discrete timeslices. Current techniques for dynamic graph drawing impose a set of timeslices on this event-based data in order to draw the dynamic graph, but it is unclear how many timeslices should be selected: too many timeslices slows the computation of the layout, while too few timeslices obscures important temporal features, such as causality. To address these limitations, we introduce a novel model for drawing event-based dynamic graphs and the first dynamic graph drawing algorithm, DynNoSlice, that is capable of drawing dynamic graphs in this model. DynNoSlice is an offline, force-directed algorithm that draws event-based, dynamic graphs in the space-time cube (2D+time). We also present a method to extract representative small multiples from the space-time cube. To demonstrate the advantages of our approach, DynNoSlice is compared with state-of-the-art timeslicing methods using a metrics-based experiment. Finally, we present case studies of event-based dynamic data visualised with the new model and algorithm.
KW - Information visualisation
KW - dynamic graphs
KW - event-based analytics
KW - graph drawing
KW - no timeslices
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U2 - 10.1109/TVCG.2018.2886901
DO - 10.1109/TVCG.2018.2886901
M3 - Article
C2 - 30575538
AN - SCOPUS:85058898178
VL - 26
SP - 2373
EP - 2386
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
SN - 1077-2626
IS - 7
M1 - 8580419
ER -