The workflow and applications used in visualization depend on the type of data that is being analyzed.

Scientific visualization

Data that has an inherent spatial context (like the flow in a channel or a molecular interaction) is visualized using the methods of scientific visualization. In this case, data is mapped to geometry. Applications typically used for this purpose include ParaView and VMD.

Common challenges in scientific visualization include:

  • Importing non-standard data into visualization applications
  • Filtering out unnecessary data
  • Shortening I/O times
  • Managing large data sets
  • Running visualization as a parallel process that utilizes many cores or graphics cards
  • Fine-tuning final visualizations for the largest impact

CSC application specialists can help with the visualization software available on our supercomputers. You can get support from our specialists via the CSC service desk.

You can also learn more about using Blender software from our tutorial series.

Data visualization

Abstract, statistical data is visualized using the methods of data visualization. Typically, such visualization is done using R or Python, and is illustrated with graphs.

Our data analysis specialists can help you in visualizing abstract, statistical data using tools such as R and ggplot2. You can reach them via our service desk as well.