Computer Science, Machine Learning, and Applied Mathematics
TimeTuesday, June 2716:00 - 18:00 CEST
DescriptionData acquisition and computing systems have evolved to produce large amounts of data, but most of these datasets contain small scale features that cannot be aggregated to be understood. While these small features are usually very hard to detect automatically, the human eye can do it almost instantly, provided that the data is presented in a visually efficient way. Visualizing data in a human-readable way not only helps with data comprehensibility, but serves both data analysis and science communication. However, visualization tools and techniques need to keep pace with both increasing data sizes and the diverse needs of the scientific community. This is why a special effort towards developing automatic data visualization has been used since for as long as computing has existed, and it is getting more and more important in the present years. The minisymposium aims at gathering people working in the field of scientific big data visualization and researchers to discuss current needs and available technologies to initiate new collaborations and ideas. It will probably arise that across different fields, similar problems have to be solved, especially regarding performance and interface design. The minisymposium will motivate the mutualization of efforts needed to tackle those problems.