Course website Data Visualization 2020 course at University of Edinburgh. Check here for updates and course materials. Learn will
be used for assignments only.
Course organizer: Dr. Benjamin Bach
Lecture:Mondays 10-11, 7 George Sq, S.1
Assignment 1: 26. February 2020, 4pm UK time
3. April 2020, updated to 10. April, updated to 14. April , 4pm UK time
T1: Critique & Redesign
- Discover common flaws and mis-interpretations of visualizations
- Create visualization guidelines
- Design improved visualizations
- Analysis (10min)
- Look at all the charts provided
- list as many flaws as you can
- 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
- 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.
- 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.
- Show visulizations on wall (20min)
T2: Challenge + Sketching
- 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:
- What is my data about?
- Where does it come from?
- How is it characterized?
- 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?
- Who is my audience?
- Why should they matter?
- What do they know about topic?
- What do they know about visualization?
- 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?
- Sketching intro: This is a quick intro by your tutor to quickly express an idea through sketching
- Time a few seconds to draw what your tutor is telling you (~4 pieces)
- Draw your home country (10sec)
- Draw population density inside (20sec)
- 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
- Get into groups of 3 students (will be facilitated). Decide on a rough topic and search for data.
- Decide which topic you want to work on (create a challenge sheet like in tutorial 2?)
- Look for data in the internet: what data do you need?
- Explore a data set of your choice, using any of the tools discussed in class (e.g., Rawgraph, Tableau, D3)
Discuss with your neighbor or group members
- which visualizations did you use?
- which insights did you find?
- how effective are the visualization you chose? What would need to be improved?
- How effective are the tool(s) you’re using? Which features and workflows are working well? Which tools and features are hard to use? Which tools would you recommend?
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.
- What is your take-home message? (–> “Insight”)
- What do you want people to do? (–> “Action”)
- Who is your audience?
- Why do they care? (–> “Curiosity”)
- What does your audience know about the topic?
- What does your audience know about visualization and data analysis?
- Write down the main points in a small story
This structure will help:
- what is topic?
- What is my data?
- why does that matter?
- Which facts do you need to communicate?
- Which visualizations do I need?
- How can I explain each visualization?
- summary of important findings
- take-home message
- Call to action, if requires
- Create either:
- a storyboard,
- the layout for an infographic,
- design + interaction for an interactive application
- walk the entire group through your findings.
1. Visualization Critique (15min)
- Bring your visualizations from Assignment 1
- Exchange your visualization and give constructive and critical feedback. Use the heuristics from the Evaluation lecture as well as all the other lectures. Give ideas for improvement
- 10min critiquing + 5min discussion
2. Checklist and evaluation of group project (30min)
- Create a checklist of at least 10 items that can be used as a heuristic to evaluate a visualization
- Exchange that checklist with another group
- Evaluate your visualization according to the checklist that you have received
- For each item on the checklist, note down:
- how much you fulfill the advice / guideline / item (1-5 Likert scale)
- what you could you do to improve
- If time permits, exchange checklists again
3. Plan evaluation of group work (50min)
- for your group project and assignment 2, create an evaluation plan & questionnaire to evaluate your visualization
- Write a piece of context about your work so that your study participants get the context
- Define tasks to ask the users (5)
- Create a questionnaire that includes:
- asking for background (if appropriate)
- asking for feedback on visualization and tasks. How you ask for feedback and what questions you ask is entirely up to you. Make sure that you have thought about:
- Which information do you need to improve your project? (e.g., can people understand X?)
- What data do you need to get this information? (e.g., can people solve task Y, associated to feature X?)
- What question to ask to get these data (e.g., ask a question Z that requires people to perform Y).