DataVis 2020

Course website Data Visualization 2020 course at University of Edinburgh. Check here for updates and course materials. Learn will be used for assignments only.


Vis Guidelines

Course organizer: Dr. Benjamin Bach
Lecture:Mondays 10-11, 7 George Sq, S.1


Assignment 1: 26. February 2020, 4pm UK time
Assignment 2: 3. April 2020, updated to 10. April, updated to 14. April , 4pm UK time


T1: Critique & Redesign


Material: Charts


  1. Analysis (10min)
    • Individually
    • Look at all the charts provided
    • list as many flaws as you can
  2. Discussion (10 min)
    • With your neighbor,
    • discuss the flaws you found
    • compile a list of common flaws/pitfalls you found.
    • Give each pitfall
      • a name (e.g., ‘Axes truncated’)
      • and an implication of how this might affect people’s (mis)interpretation (‘People will mis-interpret differences between values on the y-axis. People might misinterpret actual sizes. Etc.’)
    • Discuss faults in class


  1. Re-design (30min)
    • with your neighbor
    • pick 2 visualizations from the charts provided
    • for each visualization, sketch 2 possible redesigns
    • Argue with the guidelines (see above) and state where guidlines can be violated.
  2. Guidelines (20min)
    • with your neighbor,
    • formulate visualization guidelines to overcome these flaws/pitfals. Use careful formulations: “Do X; “Avoid Y”; “If X, then Y”; “Keep in mind that X”, etc.
  3. Show visulizations on wall (20min)

T2: Challenge + Sketching


  1. Data Challenge: Draft a data challenge for the data you might think working with in assignment #2. A data challenge describes the context for your visualization project. Take a sheet and fold it twice so you get 4 areas. In each area, write notes about the following:
    1. Data:
      • What is my data about?
      • Where does it come from?
      • How is it characterized?
    2. Messages / Insigths / Facts
      • What am I looking for in the data?
      • What is the data showing?
      • What do I want to tell to the reader?
    3. Audience:
      • Who is my audience?
      • Why should they matter?
      • What do they know about topic?
      • What do they know about visualization?
    4. Context
      • Where does the audience engage with the visualization?
      • How do they engage? * Work out the challenge alone, then discuss with your neighbor(s) * Are there people with similar data and interest in class?
  2. Sketching intro: This is a quick intro by your tutor to quickly express an idea through sketching
    1. Time a few seconds to draw what your tutor is telling you (~4 pieces)
    2. Draw your home country (10sec)
    3. Draw population density inside (20sec)
  3. Sketching data: Sketch your own data or some small data sample provided by your tutor
    • Draw 4 quick sketches (2min each)
    • Discuss with your neighbors
    • Elaborate on 1 visualization
    • Discuss in class

T3: Tools and data exploration

Discuss with your neighbor or group members

T4: Storyboarding

The tutorial will start with a brief introduction into data comics and storyboarding. Your task is to create a storyboard and narrative around your visualzation projct. In this tutorial, you will work in groups.

Tutorial Slides:

Problem analysis



T5: Evaluation

1. Visualization Critique (15min)

2. Checklist and evaluation of group project (30min)

3. Plan evaluation of group work (50min)