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InfoVis 2010 Lecture 1

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Visualizzazione dell'Informazione 2009/2010, Informatica Umanistica, Università di Pisa

Visualizzazione dell'Informazione 2009/2010, Informatica Umanistica, Università di Pisa

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  • Friendly, M. & Denis, D. J. (2001). Milestones in the history of thematic cartography, statistical graphics, and data visualization. Web document, http://www.math.yorku.ca/SCS/Gallery/milestone/. Accessed: February 23, 2010
  • Map are the fundamental form of visualization because it is connected to the real terrain
  • G-Speak
  • S. S. Stevens, On the theory of scales of measurements, 1946
  • Visual Thinking for Design , Colin Ware, Morgan Kaufman (2008)
  • Transcript

    • 1. Information Visualization Course Informatica Umanistica Università di Pisa Lecture I – 24 th February 2010 Emanuele Ruffaldi PERCRO - Scuola Superiore S.Anna
    • 2.
      • Term Visualize
      form a mental image of something to make perceptible to the mind
    • 3. Visualization in the Past http://www.math.yorku.ca/SCS/Gallery/milestone/ Oldest Known Map (Museum at Konya, Turkey) c. 6200 BC Oldest World Map by Anaximander of Miletus c. 550BC
    • 4. Visualization Today Evolution of Storage MIT, Real Time Rome Rosling @ TED New York Tube (NYT) RoamBi Enabling Technology Laboratory in the UAB School of Engineering
    • 5. Information Visualization
      • The purpose of
      • visualization is to
      • convey information to
      • people through
      • graphical means
      Pat Hanrahan, Barbara Tverski, et al.
    • 6. Visualization Goals
      • Macro Goals
        • Record
        • Analyze
        • Present
      • Effects
        • Map
        • Abstract
        • Clarify
        • Interact
        • Communicate
        • Discover
    • 7. Clarify http://homepage.ntlworld.com/clivebillson/tube/tube.html
    • 8. Clarify First Clear map of London Tube by Harry Beck in 1931 (Topology Based)
    • 9. Interaction G-Peak by Oblong
    • 10. Information Explosion
      • The Industrial Revolution of Data ( Joseph Hellerstein , UC Berkeley)
    • 11. Challenges
      • Information Explosion
        • Increasing amount of data
        • How to Select?
      • Visual Form
        • Many different ways of representing data
        • Which Visualization?
      • Interactivity
        • Interactivity improves visualization
        • Which Interaction metaphor?
    • 12. Visualization Process Data Acquisition Scraping Visualization Design Evaluation Interaction Data Processing Decision Problem Statement
    • 13. Information Model
      • Entities
        • Single elements with Attributes
      • Relationships
        • Associations between Entities
        • With their Attributes
    • 14. Representation
      • Semantic
      • Arbitrary
      • Conventional
    • 15. Data Types
      • Attribute Quality
        • Nominal (Categorical): Fruits, Colors,…
        • Ordinal (Ordered): Days, Ratings
        • Quantitative
        • Interval : time
        • Ratio
      • Attribute Dimensionality
        • Dimension like 1..2… for vector
      S. S. Stevens, On the theory of scales of measurements, 1946
    • 16. Basic Visual Encoding
      • Representations of Data
        • Position
        • Size
        • Color (shade)
        • Textures
        • Orientation
        • Shape
      • Exercise
        • How we can intuitively map types of data to such Encodings?
      • The Design Space of InfoVis is the selection of the Visual (and Interaction) Metaphors
    • 17. Basic Visual Encoding
    • 18. COURSE STRUCTURE
    • 19. Objective of this Course
      • Provide the principles and the technique for making effective visualizations
    • 20. Structure of the Course
    • 21. Foundation
    • 22.
      • Design principles for Statistics Graphs
      • Varieties of Graphs
      Charts
    • 23. Maps Real and Abstract Maps Exercises with Google Maps e Google Earth
    • 24. Trees, Graphs and Nets
      • Foundation of complex visualization
      • Used for Social Networking analysis
      • Basics of Graph Theory
      • Layout and Display
      • Exercises on the Web
      Flow Graph Tree Map
    • 25. Information Landscapes 3D Tool for Visualization
    • 26. Text Analysis Application of principles to text corpora Exercises on known large corpora as Shakespeare, Homerus …
    • 27. Patent Analysis
      • Case Study on use of Visualization for patent data
      • Graphs and Maps based
      • Citation Analysis
    • 28. Lectures
      • Lecture Types
        • Theoretical
        • Practical
        • Exercises
        • Project Discussion
      • Relevant Scientific Papers
    • 29. Textbook
      • Textbook
        • Information Visualization Perception for Design (2 nd ), Colin Ware (2004) Morgan Kauffmann
        • This first lecture is covered in Chapter 1
      • Interesting Books
        • Envisioning Information, Edward Tufte
    • 30. Practice
      • Web Visualization
        • HTML + JavaScript (Low)
        • Processing.js
      • Maps
        • Google Map e Google Earth
      • High Level Tools
        • Mondrian (Java Based)
      • 3D Visualization
        • Information Landscape
        • WebGL
    • 31. Web Visualization http://manyeyes.alphaworks.ibm.com/manyeyes/ http://processingjs.org/ http://thejit.org/
    • 32. Requirements of the Course
      • Passion about Information and Visualization
      • Web Concepts and Tools
      • Basics of Programming
      • Data Concepts
    • 33. Exam
      • Project developed during the Course
      • Integrated with one or two questions
    • 34. Contact Information
      • Emanuele Ruffaldi
        • Email [email_address]
        • Address
          • PERCRO Scuola Superiore S.Anna, Via Martiri 11
      • Schedule
        • Mer 16.15-17.45
        • Ven 14.00-16.00
        • Class: FIB-I Aula I - Polo didattico via Buonarroti
      • Website http://www.percro.org/corsi/infovis10/
    • 35. These slides are subject to the License Creative Commons Attribution-Noncommercial-Share Alike 2.5 Italy