VR Collaboration Evaluation for Scientific Data Visualizatoin

Created by Dave Song Spring 2023 

About Evaluating VR Collaboration for Scientific Data Visualization

Collaboration Evaluation for collaborative Scientific Data Visualization requires a different approach to evaluation. This is because the focus for scientific visualization should be on finding meaningful and profound insights from the dataset which was not possible with other media of data visualization. Therefore, in addition to the conventional evaluation form for the VR collaboration, this evaluation form also introduces the idea of insight-based evaluation of the system.

For the sake of VR collaboration evaluation, we are going to use the definition introduced by Saraiya, P., North, C., and Duca, K which defines an insight as “an individual observation about the data by the participant, a unit of discovery.” [1]

Collaborative insight can be categorized 3 categories

<Before Evaluation Activity>

Throughout the experiment, each group’s timekeeper will record insights and the time it took for each insight. Evaluation of each insight should be done after the evaluation activity.

<After Evaluation Activity>

[Group Evaluation]

Insight Evaluation

From the timestamp and list of insights generated during the activity,

[Individual Evaluation]

Collaboration Task Load

Likert Scale of 1-10

Mental Demand

Physical Demand


Frustration Level

System Usability for Collaboration

Likert Scale of 1-10

Interaction Evaluation

Likert Scale of 1-10

Additional Qualitative Questions


1: Saraiya, P., North, C., & Duca, K. (2005). An insight-based methodology for evaluating bioinformatics visualizations. IEEE Transactions on Visualization and Computer Graphics, 11(4), 443–456. https://doi.org/10.1109/tvcg.2005.53

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