Data Visualization

Data visualization is the visual representation of data by computer generated images. Here we focus on human principle for visual analysis of various data collections such as databases. The goal is to improve insight, understanding and/or communication of data. Data visualizations use a combination of methods from a very diverse variety of disciplines: perception, computer graphics, human computer interaction, machine learning, numerical analysis, optimization, etc.

Topics covered:

• Models of the visualization process

• Colour models and use of colour

• Information visualization

• Representation and processing of data

• Interactive visual data analysis

• Truthful data visualization.

The final grade of the course consists of the following components:

• Written Final Exam (weighting 40%)

• Group Assignment: data visualization project (weighting 60%)

Final grade calculation = 0.4 * Final Exam + 0.6 * Group Assignments

A passing final grade for the course can only be earned when for all components at least a 5.0 is earned, and the weighted final grade (rounded to .5) is at least a 6.

In case of an insufficient final result, repair options may exist in accordance with Article 17A, Times and number of examinations, sub 1, of the Teaching and Examination Regulations, for:

• Final Exam: Resit opportunity, either written or oral exam, depending on the number of students.

• Group Assignments: Repair opportunity in form of a new individual project during Q3

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 2, sub 5).