Course_Data Visualization

(19328301)

TypeLecture with Exercise
InstructorClaudia Müller-Birn
Number of Places20
RoomTakustr. 9 Lecture: SR 046 Exercise: SR 053
StartOct 18, 2018
endFeb 14, 2019
Time

Lecture: Thursday 10-12

Exercise: Monday 14-16

As the use of data in research, business and politics become increasingly important, well-designed data visualizations are needed to improve understanding, reduce human memory and support decision-making.

This course aims to familiarize students with the principles, techniques, and algorithms of data visualization.
This course teaches students the basics of the current state of data visualization. At the end of the course, students will have an understanding of the following:

1. essential visualization techniques and theory, including data models, graphical perception and methods for visual coding and interaction.
2. basic techniques and algorithms for visualizing data, including multivariate data, networks, and maps.
3. practical experience in the creation and evaluation of visualizations.

The course calls for students who are interested in using data visualization in their work as well as students who develop visualization tools and systems. Basic knowledge and willingness to learn of graphics/visualization tools (e.g., D3) and data analysis tools (e.g., R) are helpful.

In addition to participating in discussions in class, students must complete several short programming and data analysis tasks as well as a final project. Students are expected to submit the results of the project in the form of a conference paper.

Please note that the course does not include exploratory approaches to the discovery of data. Instead, the course focuses on how data is visually encoded and presented to an audience after the structure of the data and its content is known.

Text Book

Munzner, Tamara. Visualization analysis and design. AK Peters/CRC Press, 2014.

Additional Literature

  • Interactive Data Visualization for the Web, 2nd Edition. Scott Murray, O'Reilly Press. 2017. 
  • Yau, Nathan: Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley Publishing, Inc. 2011.
  • Spence, Robert: Information Visualization: Design for Interaction. Pearson. 2007.

Syllabus

  Date Lecture Topic Lecture Date Exercise Topic Exercise Homework
1 18.10.2018 What is data visualization, and why should we do it? 22.10.2018 Reading and Discussing the article: "A nested process model for visualization design and validation."  
2 25.10.2018 What: Data Abstraction 29.10.2018 Introducing Term Project Reading task description for the term project
3  01.11.2018  Why: Task Abstraction  05.11.2018 Introducing Basics of Web Development Present project idea
4  08.11.2018  Analysis: Four Levels of Validation  12.11.2018 Introducing Visualizations with D3 Work on your term project
5 15.11.2018  Marks and Channels  19.11.2018 Term Project Idea Presentation (describe algorithm and type of intended visualization approach) Morphological analysis
6  22.11.2018  Rules of Thumb  26.11.2018 Comparing existing visualization approaches based on selected dimensions Work on your term project
7  29.11.2018

 How: Arrange Tabular Data

03.12.2018 Evaluating existing approaches and user testing Work on your term project
8  06.12.2018  How: Arrange Spatial Data 10.12.2018 Basics of paper writing Work on your term project
9  12.12.2018  How: Arrange Networks + Tree 17.12.2018 How to conduct a peer review?

Carry out peer review!

10  20.12.2018  How: Map Color and Other Channels  07.01.2019  Analysis of Visualisation Case Studies Work on your term project
11  10.01.2019

 How: Manipulate View

 14.01.2019 Design Feedback Work on your term project 
12  17.01.2019  How: Facet into Multiple Views  21.01.2019 Technical Feedback Work on your term project
13  24.01.2019  How: Reduce Items and Attributes  28.01.2019 How to present your project? Work on your term project
14  31.01.2019  How: Embed: Focus + Context  04.02.2019 Open Review  
15  07.02.2019  Summary and Case Studies  11.02.2019  Class project presentation  
16 14.02.2019 Exam/Project Presentation 01.03.2019  Submission of Project Report