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Module Overview

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The documentation should include:

  • Abstract
  • Introduction into the topic and research question
  • Data analysis with sources and methodology
  • Design and development process with stages and variations
  • Result with explanation and evaluation
  • Conclusion and outlook

Grading

Grades will be based on group presentations, class participation, home assignments, documentation (journal) and final work. Contributing to constructive group feedback is an essential aspect of class participation. Regular attendance is required. Two or more unexcused absences will affect the final grade. Arriving late on more than one occasion will also affect the grade.

  • 10% Participation (Data Literacy)
  • 60% Final work (Data Visualization)
  • 30% Documentation (Data Visualization)

Any assignment that remains unfulfilled receives a failing grade.

Calendar

Week 1

Tuesday 31.10

Wednesday 1.11

Thursday 2.11

Friday 3.11




Data Literacy
09.30-17.00

4.D12, TG

Introduction

From Data to Knowledge

Data Sources

Please bring your own laptop to the course!

Data Literacy
09.30-17.00
4.D12, TG

Data Sources & Quality

Data Types / Formats

Data Tools / Working with Data



Week 2

Tuesday 7.11

Wednesday 8.11

Thursday 9.11

Friday 10.11


Data Literacy
09.30-17.00

4.D12, TG

Data Quality

More Data Tools

Geospatial Data

tbd.

Data Visualization
Introduction & Briefing

09.00-12.0
4.D12, BW, JG

Topic and Data Research

Design Input 1
Basic Techniques

09.00-12.00
4.D12, BW

Topic and Data Research

Tech Input I

09.00-12.00
4.D12, JG

Mentoring
13.00-15.00
Atelier, BW, JG

Topic and Data Research

Week 3

Tuesday 14.11

Wednesday 15.11

Thursday 16.11

Friday 17.11

B&A

Data Analysis

Data Analysis

Ideation and Concept

Ideation and Concept

Week 4

Tuesday 21.11

Wednesday 22.11

Thursday 23.11

Friday 24.11

B&A

Design Input 2
Intermediary Techniques

09.00-12.00
4.D12, BW

Mentoring
13.00-15.00
Atelier, BW, JG

Concept

Tech Input 2

09.00-12.00
4.D12, JG

Concept Finalization

Aesthetics of Interaction
09.00 - 12.00

Production

Mentoring
09.00-12.00
Atelier, BW, JG

Production

Week 5

Tuesday 28.11

Wednesday 29.11

Thursday 30.11

Friday 1.12

B&A

Production

Aesthetics of Interaction
09.00 - 12.00

Mentoring
13.00-17.00
Atelier, BW, JG

Production

Production

Presentation
09.00-12.00

4.D12, BW, JG

Documentation


TG: Timo Grossenbacher, BW: Benjamin Wiederkehr, JG: Joël Gähwiler

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InputDateContentInstructorSlides
Introduction & Briefing8.11

Data Visualization Foundation

  • Purpose
  • History
  • State of the Art
  • Future Frontiers

Briefing

  • Theme
  • Approach
  • Deliverables
  • Schedule
  • Data Sources
  • Materials
BW

Interactive Visualization — Data Visualization Foundation — Benjamin Wiederkehr (2017).pdf

Design Input 19.11

Basic Techniques

  • Data Properties
  • Human Properties
  • Graphical Encoding
  • Graphical Methods
BW
Design Input 221.11

Intermediary Techniques

  • Color
  • Interaction
  • Animation
  • Exploration
  • Explanation
BWInteractive Visualization — Intermediary Techniques — Benjamin Wiederkehr (2017).pdf
Technology Input 110.11
  • Online Tools (Plotly)
  • Data In & Out
  • Export => Illustrator
JG
Technology Input 222.11
  • Programmatic Analysis
  • Programmatic Transformation
JG

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