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Data Visualization - From a Human-Centered Perspective (Lecture Notes)

Claudia Müller-Birn

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Preface

:class: warning
These lecture notes are neither for distribution nor for reference. It is just a first draft and many resources may not be referenced yet, furthermore, images are largely missing. I update these lecture notes throughout the course. If you spot any major mistakes, let me know.

The current rapid technological development requires the processing of large amounts of data of various kinds to make them usable by humans. This challenge affects many areas of life today, such as research, business, and politics. In these contexts, decision-makers use data visualizations to explain information and its relationships through graphical representations of data. This course aims to familiarize students with the principles, techniques, and methods in data visualization and provide practical skills for designing and implementing data visualizations.

The master course «data visualization» is intended for students interested in better understanding how to critically engage with data visualization and how to design effective data visualizations reflectively.

Basic knowledge of programming (HTML, CSS, Javascript, Python) and data analysis (e.g., R) is helpful. In addition to participating in class discussions, students will complete several programming and data analysis assignments. In a mini-project, students work on a given problem. Finally, we expect students to document and present their assignments and mini-project in a reproducible manner.

Please note that the course will focus on how data is visually coded and presented for analysis after the data structure and its meaning are known. We do not explicitly cover exploratory analysis methods for discovering insights in data.

This course is highly influenced by the work of Tamara Munzner and her book Visualization Analysis & Design. In our hand library, there are exemplars available.

This course gives students a solid introduction to the fundamentals of data visualization with current insights from research and practice. By the end of the course, students will be able to

  • select and apply methods for designing visualizations based on a problem,
  • know essential theoretical basics of visualization for graphical perception and cognition,
  • know and to select visualization approaches and their advantages and disadvantages,
  • evaluate visualization solutions critically, and
  • have acquired practical skills for implementing visualizations.

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