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Introduction - Lecture 1 - Information Visualisation (4019538FNR)

Beat Signer
PRO
February 16, 2023

Introduction - Lecture 1 - Information Visualisation (4019538FNR)

This lecture forms part of the course Information Visualisation given at the Vrije Universiteit Brussel.

Beat Signer
PRO

February 16, 2023
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  1. 2 December 2005
    Information Visualisation
    Introduction
    Prof. Beat Signer
    Department of Computer Science
    Vrije Universiteit Brussel
    beatsigner.com

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  2. Beat Signer - Department of Computer Science - [email protected] 2
    February 16, 2023
    Course Organisation
    ▪ Prof. Beat Signer
    Vrije Universiteit Brussel
    PL9.3.60 (Pleinlaan 9)
    +32 2 629 1239
    [email protected]
    wise.vub.ac.be/beat-signer
    ▪ Yoshi Malaise
    Vrije Universiteit Brussel
    PL9.3.58 (Pleinlaan 9)
    +32 2 629 3487
    [email protected]
    wise.vub.ac.be/yoshi-malaise

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  3. Beat Signer - Department of Computer Science - [email protected] 3
    February 16, 2023
    Prerequisites
    ▪ Note that this is an advanced Master's level
    course and the following previous knowledge is required
    ▪ good programming skills
    ▪ It is not impossible to follow the course without these
    prerequisites, but in this case you should not complain
    about the potential additional workload!
    ▪ Note that the following courses teach principles that are
    also relevant for this course on Information Visualisation
    ▪ Human-Computer Interaction (1023841ANR)
    ▪ Next Generation User Interfaces (4018166FNR)

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  4. Beat Signer - Department of Computer Science - [email protected] 4
    February 16, 2023
    Course Goals
    ▪ After attending the course on Information Visuali-
    sation, the student has solid background knowledge
    about information visualisation (terminology, principles
    and issues, visualisation techniques, data representation
    and presentation).
    ▪ The student can design, develop and test interactive
    visualisations.
    ▪ The student can criticise existing visualisations.

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  5. Beat Signer - Department of Computer Science - [email protected] 5
    February 16, 2023
    Exercises
    ▪ The course content is further investigated in
    the exercise sessions
    ▪ exercise sessions might also be helpful for the assignment
    ▪ assistant: Yoshi Malaise
    - Group 1: Thursday 13:00–15:00, Group 2: Thursday 15:00–17:00
    ▪ Lab Session
    ▪ one of the exercise sessions is a dedicated lab session where
    you can work and get feedback on your assignment
    ▪ Additional content might be covered in exercise sessions
    ▪ strongly recommended to attend all exercise sessions!
    ▪ exam covers content of lectures and exercises

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  6. Beat Signer - Department of Computer Science - [email protected] 6
    February 16, 2023
    Course Material
    ▪ All material will be available on Canvas
    ▪ lecture slides, exercises, research papers, tutorials, ...
    ▪ Make sure that you are subscribed to the
    Information Visualisation course on Canvas
    ▪ https://canvas.vub.be/courses/28619
    ▪ Handouts are available on Canvas at least the day
    before the lecture
    ▪ Handouts are also available on the WISE website
    ▪ https://wise.vub.ac.be/course/information-visualisation

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  7. Beat Signer - Department of Computer Science - [email protected] 7
    February 16, 2023
    Lecture Schedule
    Exercise 2: Data Sources and Dataset Quality Assessment
    23
    24
    25
    26
    Lecture 2: Human Perception and Colour Theory
    Lecture 3: Data Representation
    Exercise 3: Preprocessing and Data Analysis Using Python
    Lecture 4: Analysis and Validation
    Exercise 6: Visualisation Frameworks
    D.2.06
    D.2.06
    D.2.06
    D.2.06
    E.1.05
    E.1.05
    E.1.05
    27
    28
    Lecture 1: Introduction
    22
    Exercise 1: Introduction and Discussion of Visualisations E.1.05
    Exercise 4: Analysis and Validation E.1.05
    D.2.06
    Lecture 5: Data Presentation
    Exercise 5: Visualisation in Python
    D.2.06
    E.1.05
    Lecture 6: Data Processing and Visualisation Frameworks
    Lecture 7: Design Guidelines and Principles
    Exercise 7: Visualisation in D3.js
    D.2.06
    E.1.05

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  8. Beat Signer - Department of Computer Science - [email protected] 8
    February 16, 2023
    Lecture Schedule …
    Lecture 9: View Manipulation and Reduction
    Exercise 9: Interaction and Design Guidelines with Bokeh and Plotly
    32
    33
    34
    35
    Lecture 10: Interaction
    Lecture 11: Dashboards
    Lab Session
    Lecture 12: Case Studies and Course Review
    31
    Lecture 8: Visualisation Techniques D.2.06
    E.1.05
    E.1.05
    D.2.06
    D.2.06
    D.2.06
    D.2.06
    Interim Project Presentations E.1.05
    36
    Final Project Presentations E.1.05
    29
    30
    No Lecture
    No Exercise
    No Lecture
    No Exercise
    Exercise 8: Interaction with D3.js E.1.05

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  9. Beat Signer - Department of Computer Science - [email protected] 9
    February 16, 2023
    Assignment
    ▪ Interactive information visualisation
    ▪ realisation of an interactive information visualisation
    for the domain and dataset(s) of your choice
    - various presentations and report
    - evaluated based on creativity, design principles and visualisation techniques,
    evaluation, documentation, presentations, source code, …
    ▪ Assignment handed out later this week
    ▪ group project with 3 students per group
    - send an email with the 3 group members and your team name to
    Yoshi Malaise by Monday, February 20 ([email protected])
    - final presentation (May 25), final report and code (May 28)
    ▪ assignment counts for 40% for the final grade

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  10. Beat Signer - Department of Computer Science - [email protected] 10
    February 16, 2023
    Exam
    ▪ Oral exam in English
    ▪ covers content of lectures and exercises
    ▪ counts 60% for the overall grade
    ▪ 5 mins questions about the assignment
    ▪ 15 mins questions about the course content (no preparation time)
    ▪ Overall grade = oral exam (60%) + assignment (40%)
    ▪ assignment is composed out of two grades
    - overall grade for project where students have some flexibility in distributing
    the grades (±2 points) (70%)
    - your contribution/knowledge to the project as checked in oral exam (30%)
    ▪ note that if either the grade for the oral exam or the grade for the
    assignment is lower than 8/20, then this automatically becomes
    the final grade!

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  11. Beat Signer - Department of Computer Science - [email protected] 11
    February 16, 2023
    Joseph Priestley (1769)

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  12. Beat Signer - Department of Computer Science - [email protected] 12
    February 16, 2023
    Joseph Priestley (1769) …

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  13. Beat Signer - Department of Computer Science - [email protected] 13
    February 16, 2023
    London Cholera Map by John Snow (1854)

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  14. Beat Signer - Department of Computer Science - [email protected] 14
    February 16, 2023
    London Cholera Map by John Snow (1854)

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  15. Beat Signer - Department of Computer Science - [email protected] 15
    February 16, 2023
    Florence Nightingale's Rose Diagram(1858)

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  16. Beat Signer - Department of Computer Science - [email protected] 16
    February 16, 2023
    Charles Minard (1869)
    ▪ Napoleon's March on Moscow (1812-1813)

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  17. Beat Signer - Department of Computer Science - [email protected] 17
    February 16, 2023
    London Underground, Harry Beck (1931)

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  18. Beat Signer - Department of Computer Science - [email protected] 18
    February 16, 2023
    Gapminder, Hans Rosling
    ▪ Hans Rosling working with developmental data for over
    30 years
    ▪ Gapminder demonstrated at 2007 TED talk 'The Best Stats
    You've Ever Seen'
    ▪ "Let the dataset change your mindset", Rosling 2007
    ▪ animated presentation in space and time

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  19. Beat Signer - Department of Computer Science - [email protected] 19
    February 16, 2023
    Video: The Best Stats You've Ever Seen

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  20. Beat Signer - Department of Computer Science - [email protected] 20
    February 16, 2023
    MindXpres Data Visualisation

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  21. Beat Signer - Department of Computer Science - [email protected] 21
    February 16, 2023
    Mapping 2019-nCoV

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  22. Beat Signer - Department of Computer Science - [email protected] 22
    February 16, 2023
    Australia Bushfires (2020)
    ▪ Not a satellite image!
    ▪ 3D visualisation of one
    month of data by Anthony
    Hearsey
    ▪ data collected by Nasa's
    Fire Information for Re-
    source Management System
    ▪ Information visualisation
    can be misused to deliver
    the wrong message

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  23. Beat Signer - Department of Computer Science - [email protected] 23
    February 16, 2023
    Mercator Projection

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  24. Beat Signer - Department of Computer Science - [email protected] 24
    February 16, 2023
    What is Visualisation (Vis)?
    ▪ F
    ▪ Augmentation of human capabilities
    ▪ A vis idiom is a distinct approach to creating and
    manipulating visual representations
    ▪ find best design for a particular task
    ▪ Resource limitations
    ▪ computers: computational capacity and scalability
    ▪ humans: perceptual and cognitive capacity
    ▪ displays: number of pixels
    - information density (data-ink ratio) = amount of information vs. unused space
    Computer-based visualisation systems provide visual
    representations of datasets designed to help people carry
    out tasks more effectively.
    T. Munzner

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  25. Beat Signer - Department of Computer Science - [email protected] 25
    February 16, 2023
    Why Use Visualisation?
    ▪ Human eyes have "superpowers"!
    ▪ visual system provides very high-bandwidth channel
    ▪ Visual reasoning is way faster and more reliable
    than mental reasoning
    ▪ perceptual inferences based on spatial location etc.
    ▪ External representation or "external cognition"
    ▪ augment human capacity beyond internal cognition and memory
    ▪ information can be organised by spatial location
    ▪ Summarise information without loosing details
    (details on demand)

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  26. Beat Signer - Department of Computer Science - [email protected] 26
    February 16, 2023
    Human in the Loop
    ▪ Many analysis problems are ill specified
    ▪ many possible questions to be asked
    ▪ human-in-the-loop exploration making use of human pattern
    detection
    ▪ augment human capabilities rather than replacing the
    human in the loop
    ▪ Exploratory analysis for scientific discovery (data
    analysis)
    ▪ Visualisation tools for presentation (communication)
    ▪ presenting existing knowledge

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  27. Beat Signer - Department of Computer Science - [email protected] 27
    February 16, 2023
    Computer in the Loop
    ▪ Visualisation of large datasets that might dynamically
    change over time

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  28. Beat Signer - Department of Computer Science - [email protected] 28
    February 16, 2023
    Showing Dataset Details
    ▪ Exploring a dataset to find patterns
    ▪ not possible if we only see a summary of the dataset
    ▪ Assessing the validity of a statistical model
    ▪ does the model fit the data?
    ▪ Statistical characterisation (descriptive statistics) of a
    dataset loses information through summarisation
    ▪ single summary often an oversimplification hiding the true
    structure of a dataset
    ▪ e.g. Anscombe's Quartet

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  29. Beat Signer - Department of Computer Science - [email protected] 29
    February 16, 2023
    Anscombe's Quartet
    [Visualization Analysis & Design, Tamara Munzner, 2014]

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  30. Beat Signer - Department of Computer Science - [email protected] 30
    February 16, 2023
    Anscombe's Quartet …

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  31. Beat Signer - Department of Computer Science - [email protected] 31
    February 16, 2023
    Interactivity
    ▪ Interactivity is necessary for vis tools handling complexity
    ▪ limitations of people and displays make it impossible to show a
    large dataset at once
    ▪ change level of details
    ▪ show different aspects of a dataset
    ▪ different representations and summaries of data
    ▪ different presentations of data

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  32. Beat Signer - Department of Computer Science - [email protected] 32
    February 16, 2023
    Difficulties in Design
    ▪ Main issue is that the vast majority of the possibilities in
    the design space will be ineffective for any specific
    usage context
    ▪ Design might be a poor match with the human
    perceptual and cognitive system
    ▪ Design might be a bad match with the intended task
    ▪ Design alternatives: consider multiple alternatives and
    choose the best one!

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  33. Beat Signer - Department of Computer Science - [email protected] 33
    February 16, 2023
    Search Space Metaphor for Vis Design
    [Visualization Analysis & Design, Tamara Munzner, 2014]

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  34. Beat Signer - Department of Computer Science - [email protected] 34
    February 16, 2023
    What-Why-How Question
    ▪ What data is shown
    ▪ Why is the visualisation tool used (task)
    ▪ How is the vis idiom constructed in terms of design
    choices

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  35. Beat Signer - Department of Computer Science - [email protected] 35
    February 16, 2023
    Information Visualisation Process
    Data
    Representation
    Data
    Data
    Presentation
    Interaction
    mapping
    perception and
    visual thinking

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  36. Beat Signer - Department of Computer Science - [email protected] 36
    February 16, 2023
    Exercise 1
    ▪ Introduction and Discussion of Visualisations

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  37. Beat Signer - Department of Computer Science - [email protected] 37
    February 16, 2023
    Further Reading
    ▪ Parts of this lecture are based on the
    book Visualization Analysis & Design
    ▪ chapter 1
    - What's Vis and Why Do It?

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  38. Beat Signer - Department of Computer Science - [email protected] 38
    February 16, 2023
    References
    ▪ Visualization Analysis & Design, Tamara
    Munzner, Taylor & Francis Inc, (Har/Psc edition),
    November 2014,
    ISBN-13: 978-1466508910
    ▪ Information Visualization: Perception for Design,
    Colin Ware, Morgan Kaufmann (3rd edition),
    May 2012,
    ISBN-13: 978-0123814647
    ▪ Envisioning Information, Edward R. Tufte,
    Graphics Press (1st edition)
    December 1990,
    ISBN-13: 978-0961392116

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  39. Beat Signer - Department of Computer Science - [email protected] 39
    February 16, 2023
    References ...
    ▪ Semiology of Graphics: Diagrams, Networks,
    Maps, Jacques Bertin, ESRI PR (1st edition),
    January 2010,
    ISBN-13: 978-1466508910
    ▪ Data Visualization: A Practical Introduction,
    Kieran Healy, Princeton University Press,
    January 2019,
    ISBN-13: 978-0691181622
    ▪ The Functional Art: An Introduction to Information
    Graphics and Visualization, Alberto Cairo,
    New Riders (Pap/Dvdr edition), August 2012,
    ISBN-13: 978-0321834737

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  40. Beat Signer - Department of Computer Science - [email protected] 40
    February 16, 2023
    References …
    ▪ Factfulness: Ten Reasons We're Wrong
    About The World – And Why Things Are Better
    Than You Think, Hans Rosling et al., April 2018,
    ISBN-13: 978-1119547259
    ▪ Mapping 2019-nCoV
    ▪ https://systems.jhu.edu/research/public-health/ncov/
    ▪ Australia Bush Fires
    ▪ https://www.sbs.com.au/news/how-fake-bushfire-images-and-misleading-
    maps-of-australia-are-spreading-on-social-media
    ▪ beautiful news daily
    ▪ https://informationisbeautiful.net/beautifulnews/

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  41. Beat Signer - Department of Computer Science - [email protected] 41
    February 16, 2023
    References …
    ▪ Gapminder
    ▪ https://www.gapminder.org
    ▪ https://www.youtube.com/watch?v=usdJgEwMinM
    ▪ https://www.youtube.com/watch?v=Z8t4k0Q8e8Y
    ▪ B. Shneiderman, Data Visualization’s Breakthrough
    Moment in the COVID-19 Crisis, 2020
    ▪ https://medium.com/nightingale/data-visualizations-breakthrough-
    moment-in-the-covid-19-crisis-ce46627c7db5
    ▪ R. Roels, Y. Baeten and B. Signer, Interactive and
    Narrative Data Visualisation for Presentation-based
    Knowledge Transfer, Communications in Computer and
    Information Science (CCIS), 739, 2017
    ▪ https://beatsigner.com/publications/roels_CCIS2017.pdf

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  42. 2 December 2005
    Next Lecture
    Human Perception and Colour Theory

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