Lecture: Visual Data Analysis


  • Lecturer(s):
  • Start: April 13, 2021 (online)
  • Dates: Tue and Wed 10:15-11:45 (online)
  • Curriculum: Master , B-IT Master Media Informatics
  • Exams: TBA



This year, the lecture will be held online, using zoom and the eCampus platform. Please sign up there to receive all relevant information.

Ever-increasing amounts of measured, simulated, collected and stored data that arise in various fields - including science, business, and journalism - have turned the ability to make sense of large and complex data into a key qualification. Visual Data Analysis provides an intuitive, effective, and thus very popular strategy for quite literally gaining insight into complex phenomena. It creates interactive visual representations of data that facilitate its exploration and analysis, communication of the findings, and steering of simulations or measurements.This lecture covers important concepts, perceptual foundations, as well as many different methods for Visual Data Analysis. In particular, this year's topics include:

  • Visualizing multi-dimensional data directly
  • Visualizing multi-dimensional data via dimensionality reduction
  • Visualizing trees and graphs
  • Perceptional foundations and effective use of color
  • Guidelines for effective visualization design
  • Visualization of deep neural networks
  • Direct volume rendering (for 3D data such as medical CT or MRI)
  • Extracting surfaces from volumetric data
  • Visualizing vector fields, such as flow fields from computational fluid dynamics
  • Visualizing matrix (tensor) fields, as they arise in engineering and modern neuroimaging