Interactive visual data exploration and analysis is an increasingly important tool and technique in big data analytics tasks. In this course we will cover the fundamental concepts of interactive data visualization, including brief reviews of important preliminary or complementary data processing techniques, color models, visual perception as well as data analysis techniques. The aim is to learn the fundamental principles and techniques of interactive data visualization, and in particular to get an overview over the different visualization techniques and categories available for the various types of data to be displayed, with a focus on multivariate data visualization.
This module primarily focuses on visual data representation and basic visualization concepts. The lecture is targeted at students with an assessment level BSc in computer science or similar basic knowledge of computer science, programming, data structures, algorithms and math. It is recommended for BSc students in the 3rd or higher semester.
|Introduction and history||||1|
|Fundamental data processing||||2|
|Visualizing quantitative data||||12|
|Multivariate data visualization||||7|
|Dimensionality reduction and clustering||||6.6, 6.9|
|Spatial data visualization|| and ||5 and 14|
|Geospatial data visualization||||6|
Main course textbooks:
 Interactive Data Visualization: Foundations, Techniques and Aplications by Ward, Grinstein and Keim, AK Peters, 2010.
Selected book chapters from:
 Mathematical Principles for Scientific Computing and Visualization by Farin and Hansford, AK Peters, 2008
 Information Visualization: Perception for Design by Colin Ware, Morgan Kaufmann, 2013.
 Interactive Visual Data Analysis by Christian Tominski and Heidrun Schumann, AK Peters, 2020.
 Visualization Analysis and Design by Tamara Munzner, AK Peters.
As a standing homework assignment you are expected to review the corresponding book chapters in  matching the lectures.
As a standing homework assignment you are expected to read the corresponding book chapters before the lectures and to review the material thoroughly after the lectures covering them.
To complete the lecture, students must also complete any exercises given in class or distributed on OLAT. Programming projects must be completed and submitted exactly in the appropriate form as indicated in the exercise requirements via OLAT to the assistant leading the exercises.
The lecture will be completed with a written exam at the end of the semester. The exam is scheduled according to the standard UZH/OEC/IFI regulations. See also the course catalogue link at the top of the page.