TY - JOUR
T1 - On the Readability of Abstract Set Visualizations
AU - Wallinger, Markus
AU - Jacobsen, Ben
AU - Kobourov, Stephen
AU - Nollenburg, Martin
N1 - Funding Information:
The authors would like to thank all of the participants in our experiment, and especially the experts of our pilot study (Daniel Archambault, Helen Purchase, Silvia Miksch). This work is supported by NSF grants CCF-1740858, CCF-1712119, and DMS-1839274 and by the Vienna Science and Technology Fund (WWTF) through project ICT19-035.
Publisher Copyright:
© 1995-2012 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - Set systems are used to model data that naturally arises in many contexts: social networks have communities, musicians have genres, and patients have symptoms. Visualizations that accurately reflect the information in the underlying set system make it possible to identify the set elements, the sets themselves, and the relationships between the sets. In static contexts, such as print media or infographics, it is necessary to capture this information without the help of interactions. With this in mind, we consider three different systems for medium-sized set data, LineSets, EulerView, and MetroSets, and report the results of a controlled human-subjects experiment comparing their effectiveness. Specifically, we evaluate the performance, in terms of time and error, on tasks that cover the spectrum of static set-based tasks. We also collect and analyze qualitative data about the three different visualization systems. Our results include statistically significant differences, suggesting that MetroSets performs and scales better.
AB - Set systems are used to model data that naturally arises in many contexts: social networks have communities, musicians have genres, and patients have symptoms. Visualizations that accurately reflect the information in the underlying set system make it possible to identify the set elements, the sets themselves, and the relationships between the sets. In static contexts, such as print media or infographics, it is necessary to capture this information without the help of interactions. With this in mind, we consider three different systems for medium-sized set data, LineSets, EulerView, and MetroSets, and report the results of a controlled human-subjects experiment comparing their effectiveness. Specifically, we evaluate the performance, in terms of time and error, on tasks that cover the spectrum of static set-based tasks. We also collect and analyze qualitative data about the three different visualization systems. Our results include statistically significant differences, suggesting that MetroSets performs and scales better.
KW - quantitative evaluation
KW - set visualization
KW - usability study
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U2 - 10.1109/TVCG.2021.3074615
DO - 10.1109/TVCG.2021.3074615
M3 - Article
C2 - 33914684
AN - SCOPUS:85105058814
VL - 27
SP - 2821
EP - 2832
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
SN - 1077-2626
IS - 6
M1 - 9418624
ER -