Scientific Data Visualization

November 2015

Scientific data usually involves many variables, often evolving dynamically, and requiring high-dimensional representation. Using visualization to effectively manipulate the data can prove challenging. In this workshop we began exploring novel methods of scientific visualization. Apart from post-processing, is there potential to use visualization even as a basis for models? Shravan Veerapaneni lead the discussion, and Eric Maslowski from the U-M 3d lab gave a brief talk about the university’s resources and how they can be used to improve our visualization methods.