DocumentCode
1818193
Title
The mental map and memorability in dynamic graphs
Author
Archambault, Daniel ; Purchase, Helen C.
Author_Institution
Clique Strategic Res. Cluster, Univ. Coll. Dublin, Dublin, Ireland
fYear
2012
fDate
Feb. 28 2012-March 2 2012
Firstpage
89
Lastpage
96
Abstract
In dynamic graph drawing, preserving the mental map, or ensuring that the location of nodes do not change significantly as the information evolves over time is considered an important property by algorithm designers. Many prior experiments have attempted to verify this principle, with surprisingly little success. These experiments have used several different algorithmic methods, a variety of graph interpretation questions on both real and fabricated data, and different presentation methods. However, none of the results have conclusively demonstrated the importance of mental map preservation on task performance. Our experiment measures the efficacy of the dynamic graph drawing in a different manner: we look at how memorable the evolving graph is, rather than how easy it is to interpret. As observed in the previous studies, we found no significant difference in terms of response time or error rate when preserving the mental map. While preserving the mental map is a good idea in principle, we find that it may not always support performance. However, our qualitative data suggests that, in terms of the user´s perception, preserving the mental map makes memorability tasks easier. Our qualitative data also suggests that there may be two features of the dynamic graph drawing that may assist in their memorability: interesting subgraphs that remain visible over time and interesting patterns in node movement. The former is supported by preserving the mental map while the latter is not.
Keywords
data visualisation; graph theory; information systems; algorithm designers; algorithmic methods; dynamic graph drawing; evolving graph; fabricated data; graph interpretation questions; memorability; mental map preservation; presentation methods; qualitative data; Animation; Context; Educational institutions; Error analysis; Heuristic algorithms; Time factors; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Visualization Symposium (PacificVis), 2012 IEEE Pacific
Conference_Location
Songdo
ISSN
2165-8765
Print_ISBN
978-1-4673-0863-2
Electronic_ISBN
2165-8765
Type
conf
DOI
10.1109/PacificVis.2012.6183578
Filename
6183578
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