New NSF Grant to Study Visualization and Causal Inference
VACLab members David Gotz and David Borland have secured a new award from the National Science Foundation (NSF) to study visual causal inference.
VACLab-ers David Gotz and David Borland have been awarded a new $1.2m grant from the National Science Foundation (NSF) to support a four-year research project aimed at improving the way in which people make causal inferences from data visualizations. This new VACLab project will study the ways in which current data visualization methods can lead people to interpret visualized patterns as indicators of causal relationships between visualized variables. People often make inferences of causality based on visualizations even when such conclusions are not supported by the data. This can lead people to draw the wrong conclusions even when visualizations are used to accurately represent the underlying data. In addition, the project will develop and evaluate new methods that intend to help improve the validity of causal inferences made by users of interactive visualization-based data exploration and analysis tools.
More information about this new NSF award can be found in the official SILS announcement of the new funding.