BaVA: Bayesian Visual Analytics
The goal of this project is to enable end users to directly manipulate data visualizations created by mathematical models for dimension reduction. Users can explore structure in high-dimensional data by directly moving data points within the visualization, causing the models to learn from the user feedback, and viewing the effects of those movements on other points.
Also known as Object-Level Interaction (OLI) and Visual-to-Parametric Interaction (V2PI).
See also Semantic Interaction.
Endert A, Han C, Maiti D, House L, Leman S, North C. Observation-level interaction with statistical models for visual analytics. In: Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on. Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on. ; 2011. p. 121 -130.
Hu X, Bradel L, Maiti D, House L, North C, Leman S. Semantics of Directly Manipulating Spatializations. IEEE Transactions on Visualization and Computer Graphics. 2013;19(12):2052 - 2059.
Leman S, House L, Maiti D, Endert A, North C. Visual to Parametric Interaction (V2PI). PLoS ONE. 2013;8(3):e50474.