This document discusses how visualization can help users understand and analyze data. It provides examples of visualizations created at KTH to analyze EU Horizon 2020 funding data, transportation systems, water usage, and education impacts. The document emphasizes the importance of understanding the user and their tasks, collecting and structuring the relevant data, and designing visualizations that effectively support the analysis process through an iterative user-centered approach. Collaboration opportunities for student thesis projects focusing on visualization design and evaluation are also mentioned.
3. Johan Blaus ∙ KTH Industry Liaison
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4. Johan Blaus ∙ KTH Industry Liasson
Linda Bell
Head of EU R&D Relations
Katrin Danerlöv
International Department Unit
National Contact Point (NCP)
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6. 6Romero: What can Visualization do for You?2016-11-08
Uber Rides (chord diagram), Cofee Flavour (sun burst), Nutrient Data (parallel coordinates), Map of the Market (treemap)
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Other Links: nutrition data, tutorials, car data, gitHut, gitHub, angular brushing, edge-bundling
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17. Horizon2020
• EU Research & Innovation program
• Largest ever!
• €80 billion of funding
• 7 years (2014 to 2020)
• Ideas (Lab Market)
• Very Competitive!
Link
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Stairway to Excellence project: Choropleth Map of Europe visualizing H2020 Funding per Capita per Region
20. How did the project succeed?
• Good students
• Commitment from client
• Time
• Funding
• Good leadership
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21. What is Visualization? “The use of computer-supported, interactive
visual representations of data to amplify
cognition.”
Card, Mackinlay, Shneiderman 1998
The art of helping people paint ideas from data.
Romero 2016
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22. Why Visualization?
Anscombe’s Quartet
I II III IV
x y x y x y x y
10 8.04 10 9.14 10 7.46 8 6.58
8 6.95 8 8.14 8 6.77 8 5.76
13 7.58 13 8.74 13 12.74 8 7.71
9 8.81 9 8.77 9 7.11 8 8.84
11 8.33 11 9.26 11 7.81 8 8.47
14 9.96 14 8.1 14 8.84 8 7.04
6 7.24 6 6.13 6 6.08 8 5.25
4 4.26 4 3.1 4 5.39 19 12.5
12 10.84 12 9.13 12 8.15 8 5.56
7 4.82 7 7.26 7 6.42 8 7.91
5 5.68 5 4.74 5 5.73 8 6.89
Mean 9 7.5 9 7.5 9 7.5 9 7.5
Variance 11 4.1 11 4.1 11 4.1 11 4.1
X-Y Correlation 0.63 0.63 0.63 0.63
Lin. Regression y = 3.00 + 0.500x y = 3.00 + 0.500x y = 3.00 + 0.500x y = 3.00 + 0.500x
0
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14
0 2 4 6 8 10 12 14 16 18 20
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x
II
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0 2 4 6 8 10 12 14 16 18 20
y
x
IV
0
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y
x
III
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y
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I
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24. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
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26. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
• Funding Analysts
• Research Officers
• Organizations
• Countries
• Policy Makers
• Grant Applicants
• Evaluation Committees
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Linda
Katrin
27. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
• Monitor participation
• Show collaboration
• Provides overview
• Create Reports
• Communicate
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28. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
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32. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
• Tree
• Sunburst
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Data: structure (hierarchy)
* 7 pillars in the database, as certain programmes are listed as pillars.
** signed projects, eCORDA H2020 database, september 30, 2016.
35. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
• Evaluation
• Test v1 experimental design:
• Tasks
• Short
• Well-defined
• Measurable results
• Test v2 descriptive/relational
design:
• Let user choose their
own task
• Deeper understanding of
the user, more realistic
feedback.
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36. Visualization Questions 1. Who is the user?
2. What are the tasks?
3. What is the data?
4. What are the visual structures?
5. How does the visualization support the tasks?
6. How can it be improved?
• Text search on abstract
• Topics
• Motivations
• Challenges
• Applications
• Deployment Data
• Usage
• Communication
• New user types
• More visual structures
• Maps
• Tree maps
• Graphs
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Requirements Design
ImplementationEvaluation
Iterative
User-Centered Design UCD
User
43. Outline
What is
Visualization
Why
Visualization
Why Human-
Centered?
Examples
Viz-A-Vis
Open Questions
Visualization
Sustainable
Development
Examples
Nairobi Water
Open Questions
Mixed Reality
Visualization
What is Mixed
Reality?
Examples
Spinnulator
Open Questions
Expo-Based
Learning
What is it?
Current Results
Closing
Summary
News
Students venturing through startups.
Erik Dahlberg’s start up Tidebanan 2015
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54. What can Visualization
do for you?
• Discover who the user is
• Unearth the user tasks
• Formalize a data model
• Map data into visual structures
• Program interactive visualizations
• Evaluate Results
• Help you discover questions you
didn’t know you had
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55. How can we
collaborate?
• MS Thesis
• Proposal – exjobb portal
• Visualization Goal
• User
• Tasks
• Data
• Student Competencies
• 800 Hrs
• Supervision
• Funding is optional
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