S6.1+2 Foundations of Data Visualization

As said in the beginning, this second part is about creating and understanding data visualizations. It will be run by me, Benjamin Bach.

The learning outcomes of this 2nd cours are as follows, and tested in the 3rd Assignment (40%).

  1. Interpretation: Correctly interpret non-standard visualizations
  2. Critique: Critically judge its visualization design with respect to deception and perception flaws.
  3. Design: Create an appropriate and informed (re)design of a visualization for a specific context and data set.

The visualization lecture part will be less of a flipped classroom but contain more traditional lectures. However, in order to prepare the lectures and better follow their content, i recommend you to read through a paper for some of the sessions. Rather than being textbook chapters, the papers are scientific articles. This might a bit harder to read in the beginning but much of the knowledge in data visualization is (unfortunately) still packed in papers and the area is evolving rapidly. Thus, once you are familiar with reading these kind of papers, you will have opened your self a great source of knowledge. However, I do not expect you to read through any of the papers entirely and in great detail. I want you to understand the high-level ideas in these papers and to have a think about the respective concepts before class. The lectures then builds on the concepts in the respective papers and extend them. My slides will be up after the lecture.

For each lecture, there will be a new forum where you can pose questions and issues you want to discuss during the lecture. Questions are anonymous and I will pick some/the most urgent of them and try to discuss them in class at a given point.

6.1 Foundations of Data Visualization (Tuesday)

The first lecture (Tuesday, February 25, 6.1 Foundations of Data Visualization) will give a high-level introduction into the What, Why, and How of data visualization as well as discusses some of the intrinsic principles for visualization. Please, familiarize yourself with the ‘visual variables’ as described by Sheelagh Carpendale. I recommend reading until Section 4 including, and then browse through the individual variables to understand which they are. You do not need to read the entire paper beyond Section 4 on.

My lecture slides are here. Download a copy if you like to preserve them:THF-2019-1-introduction to vis

Additional optional readings on topics in this lecture include:

  • Jaques Bertin: The Semiology of Graphics
    • Chapter: General Theory
    • Chapter: The Properties of the Graphic System
  • Tamara Munzner: Visualization Analysis & Design
    • Chapter 2: What-Data Abstraction (Be careful as Munzner uses some different terminology and categorization. There is no true consensus in the field).
    • Chapter 5: Marks and Channels
  • Colin Ware: Perception for Design
  • Wong: Gestalt Principles I, Nature Methods, 2010
  • Wong: Gestalt Principles II, Nature Methods, 2010
  • Nature Methods on Data Visualization

6.2 Tasks and Scenarios (Wednesday)

For the 2nd session on Wednesday, I’d like you to have a look at a paper on tasks in visualization. Again, this paper will be the basis for the class and I recommend reading the following three sections so we can discuss the remainder of the paper in class.

  • 1. Introduction
  • 2. related Work
  • 4. An Analytic Task Taxonomy

Slides can be found here: THF-2019-2-Tasks&Scenarios.

References for this lecture:

  • Lee, B., Plaisant, C., Parr, C. S., Fekete, J. D., & Henry, N. (2006, May). Task taxonomy for graph visualization. In Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization(pp. 1-5). ACM.
  • Andrienko, N., & Andrienko, G. (2006). Exploratory analysis of spatial and temporal data: a systematic approach. Springer Science & Business Media.
  • Ahn, J. W., Plaisant, C., & Shneiderman, B. (2014). A task taxonomy for network evolution analysis. IEEE transactions on visualization and computer graphics, 20(3), 365-376.
  • Peuquet, D. J. (1994). It’s about time: A conceptual framework for the representation of temporal dynamics in geographic information systems. Annals of the Association of american Geographers, 84(3), 441-461.
  • Bach, B., Pietriga, E., & Fekete, J. D. (2014). Graphdiaries: Animated transitions andtemporal navigation for dynamic networks. IEEE transactions on visualization and computer graphics, 20(5), 740-754.
  • Aigner, W., Miksch, S., Schumann, H., & Tominski, C. (2011). Visualization of time-oriented data. Springer Science & Business Media.