Abstract
As the world becomes more complex and plagued by wicked problems, there is an increased need for more multifaceted visual frameworks to untangle and clarify global issues. Budgets, census outcomes, stock market results, and other statistical data are best understood and explored through comparison, however to date there has been no effective visual solution framework for assessing a variety of hierarchal data sets. TreeVersity, a new interactive framework, is changing this. TreeVersity facilitates visual comparisons for hierarchical data, revealing trends, significant changes and other data revelations through multiple tree visualizations. The framework enables comparison within small, 10-node data sets to those with as many as 1,000,000 data points or more; it can reveal both overall structural changes such as the addition and removal of nodes and the differences in the node attributes including absolute and relative changes. TreeVersity is a user-centric program that delivers control of information to its users, allowing them to select, prioritize, recast and narrate the story they want data sets to tell. It offers customization of color ranges as well as the expansion or deletion of visual nodes based upon a user’s desired data-significance range. Users can quickly discover relevant information through framework interaction that includes realtime highlighting of hyperlinked relevant nodes and branches. TreeVersity offers both macro and micro views of comparison data through the dynamic progressive exposure of information, as dictated by the user. The project has progressed significantly, and TreeVersity collaborators will continue to develop the framework. In this paper, we will present TreeVersity through data visualizations as well as outline the visual system’s in-progress expansion possibilities.
Keywords
information visualization, tree comparisons
Citation
Guerra Gómez, J., Buck-Coleman, A., Plaisant, C., and Shneiderman, B. (2012) TreeVersity: Visualizing hierarchal data for value with topology changes, in Israsena, P., Tangsantikul, J. and Durling, D. (eds.), Research: Uncertainty Contradiction Value - DRS International Conference 2012, 1-4 July, Bangkok, Thailand. https://dl.designresearchsociety.org/drs-conference-papers/drs2012/researchpapers/46
TreeVersity: Visualizing hierarchal data for value with topology changes
As the world becomes more complex and plagued by wicked problems, there is an increased need for more multifaceted visual frameworks to untangle and clarify global issues. Budgets, census outcomes, stock market results, and other statistical data are best understood and explored through comparison, however to date there has been no effective visual solution framework for assessing a variety of hierarchal data sets. TreeVersity, a new interactive framework, is changing this. TreeVersity facilitates visual comparisons for hierarchical data, revealing trends, significant changes and other data revelations through multiple tree visualizations. The framework enables comparison within small, 10-node data sets to those with as many as 1,000,000 data points or more; it can reveal both overall structural changes such as the addition and removal of nodes and the differences in the node attributes including absolute and relative changes. TreeVersity is a user-centric program that delivers control of information to its users, allowing them to select, prioritize, recast and narrate the story they want data sets to tell. It offers customization of color ranges as well as the expansion or deletion of visual nodes based upon a user’s desired data-significance range. Users can quickly discover relevant information through framework interaction that includes realtime highlighting of hyperlinked relevant nodes and branches. TreeVersity offers both macro and micro views of comparison data through the dynamic progressive exposure of information, as dictated by the user. The project has progressed significantly, and TreeVersity collaborators will continue to develop the framework. In this paper, we will present TreeVersity through data visualizations as well as outline the visual system’s in-progress expansion possibilities.