Section outline

  • The lectures on Data Visualization start on Friday, November 20. We will continue with the established schedule, that is Monday and Fridays from 9:00 to 11:00. All lectures will be online only. You can access the Teams here.

    All students that were members of the Information Retrieval Team are also members of the Data Visualization Team. If a mistake was made and this is not the case, let me know.

    • Sources of data File PDF

      A collection of various freely available data sources

    • Lesson 1

      Course introduction

      Foundations

      • What is data visualization
      • Why visualize data
      • Historical visualizations
    • Introduction File PDF
    • Foundations File PDF
    • Assignment 1 File PDF
    • Lesson 2

      Foundations

      • The three principles of good visualization design

      Data abstraction

      • Dataset types

    • Data abstraction File PDF
    • Task abstraction File PDF
    • Assignment 2 File PDF
    • Lesson 3

      Data abstraction

      • Attribute types and semantics

      Task abstraction
      • Goals and tasks
      • Actions and targets

      Human visual perception
      • Motivation
      • Memory
      • Visual encoding
      • Channel accuracy
    • Lesson 4

      Human visual perception

      • Channel discriminability
      • Channel salience (pop-out)
      • Channel separability
      • Grouping
      • Visual order
    • Human visual perception (part 1) File PDF
    • Lesson 5

      Human visual perception

      • Color perception
      • Color specification
    • Lesson 6

      Human visual perception

      • Color use: color maps, semantics of color, considerations for color blind people, the importance of size and contrast
    • Human visual perception (part 2) File PDF
    • Lesson 7

      Human visual perception

      • Color use: importance of background and surrounding color, choosing color

      Visualization design
      • The seven steps of visualization design
      • Basic charts: line, bar and pie charts, dot and choropleth maps
    • Visualization design File PDF
    • Lesson 8

      Visualization design

      • Basic charts: tile maps, node-link diagrams and adjacency matrices
      • Visualizing multidimensional data
      • Visualizing uncertain data
    • Assignment 3 File PDF

      The description of the third assignment

    • Assignment 3 data File XLSX

      The data for the third assignment

    • Lesson 9

      Visualization design

      • Visualizing missing data
      • Using interactivity for data adjustments and presentation adjustments
      • Examples of interaction, animation and storytelling
      • Visualization tools (D3, Tableau)

      Examples of (un)trustworthy visualizations
      • Visualizations using dubious data
    • Lesson 10

      Reviewing the results of the third assignment

      Information about the exam

      Examples of (un)trustworthy visualizations

      • Ignoring conventions
      • Abusing scales
    • Assignment 3 results File PDF

      Results of the third assignment

    • Exam File PDF

      Information about the exam

    • Lesson 11

      Python libraries needed for hands-on lessons (Plotly and Dash)

      Examples of (un)trustworthy visualizations

      • Improper categorization
      • Oversimplifying
      • Ignoring uncertainty
      • Confirmation bias

      Examples of (in)accessible visualizations
    • Python libraries for hands-on lessons File PDF
    • Test Plotly File IPYNB
    • Test Dash File IPYNB
    • Examples of (un)trustworthy visualizations File PDF
    • Examples of (in)accessible visualizations File PDF
    • Lesson 12

      How to create accessible visualizations

      Visualizing COVID-19

      Hands-on example in Python

      • The Plotly library
      • Recreating the interactive Gapminder bubble chart
    • Visualizing COVID-19 File PDF
    • Gapminder data File CSV
    • Gapminder data info File CSV
    • Gapminder data mini File CSV
    • Plotly Basics File IPYNB
    • Gapminder hands-on 2021-01-11 File IPYNB
    • Lesson 13

      Hands-on example in Python

      • Adding animation to the Gapminder bubble chart
      • The Dash library
      • Using dropdowns to select axes of the chart
    • Gapminder hands-on 2020-01-15 File IPYNB