Data visualization enables insight, verification, and communication for presentations and publications. Visualization is closely tied to analyzing and exploring data generated by simulations and acquired in experiments. Animation is effective for representing complex behavior of variables over time. We will present software tools and techniques available for scientific visualization. Python’s matplotlib graphics can be incorporated into computational workflows. Interactive programs such as VisIt and Paraview have a graphical user interface for exploring and displaying data. This software is freely available for Mac, Windows, and Linux platforms and is installed on the Princeton University High Performance Computing Systems. PICSciE’s remote visualization capability enables using personal computers to look at large amounts of data kept on the Research Computing storage system.
The session assumes no prior experience with visualization tools. It is intended for researchers interested in developing visual representations of their data.