CPSC 371 Syllabus

Week 1: 1/15-1/19

Topics: course overview and introduction; the power of representation; about data, perception, and visual structures

Reading:

• [Wed] (wiki page)
  • Card, Mackinlay, Shneiderman. Information Visualization, chapter 1, pages 1-17.
• [Fri] (wiki page)
  • Card, Mackinlay, Shneiderman. Information Visualization, chapter 1, pages 17-34.

Additional Reading: (optional)

• Tufte. Visual Explanations, pages 38-53. (wiki page)
• Zhang, Norman. "The Representation of Numbers", Cognition, 57, pp. 271-295, 1995. (wiki page)

Lecture Slides:

• [Mon] Introduction
• [Wed] The Power of Representation
• [Fri] About Data

Week 2: 1/22-1/26

Topics: visual variables; representing variables, values, objects, and relationships; space and color

Reading:

• [Mon] no reading
• [Wed] (wiki page)
  • Healey. Perception in Visualization.
  • Cleveland, McGill. "Graphical perception and Graphical Methods for Analyzing Scientific Data", Science, New Series, vol. 229, no. 4716 (Aug. 30, 1985), pp. 828-833.
• [Fri] (wiki page)
  • Tufte. Envisioning Information, pages 81-96.
  • Rogowitz, Treinish. "Why Should Engineers and Scientists Be Worried About Color?" or Rogowitz, Treinish. "How Not to Lie with Visualization", Computers in Physics, 10(3) May/June 1996, pages 268-273.

Additional Reading: (optional)

• Cleveland, McGill. "Graphical perception: Theory, experimentation and the application to the development of graphical models", Journal of the American Statistical Association, 79:387 (September 1984), pp. 531-554. (wiki page)

Lecture Slides:

• [Mon, Wed, Fri] Mapping Variables to Visual Structures
• [Fri] Color

Handouts:

• hw1: summary of comments

Week 3: 1/29-2/2

Topics: color; software lab

Reading:

• [Mon] no reading
• [Wed] (wiki page)
  • prefuse documentation
• [Fri] no reading

Lecture Slides:

• [Mon, Wed] Color

Week 4: 2/5-2/9

Topics: representing objects and relationships; space; technique toolbox

Reading:

• [Mon] (wiki page)
  • Tufte. Visual Explanations, "Images and Quantities", pages 13-26.
• [Wed] (wiki page)
  • Tufte. The Visual Display of Quantitative Information, "Graphical Excellence", pages 13-52.
• [Fri] (wiki page)
  • Tufte. Envisioning Information, "Escaping Flatland", pages 12-36.

Lecture Slides:

• [Mon] Representing Objects and Relationships, Space
• [Wed] The Display of Multivariate Data
• [Fri] Discussion

Week 5: 2/12-2/16

Topics: technique toolbox; graphical integrity and graphical excellence

Reading:

• [Mon] (wiki page)
  • Tufte. The Visual Display of Quantitative Information, "Chartjunk: Vibrations, Grids, and Ducks", pages 106-121.
• [Wed] (wiki page)
  • Tufte. The Visual Display of Quantitative Information, "Graphical Integrity", p. 53-77.
• [Fri] (wiki page)
  • Stephen Few. "Graph Designs for Rapidly Assessing Budget Performance".
  • Stephen Few. "Graph Designs for Reviewing Transactions and the Changing Balance".
  • Stephen Few. "Simple Displays of Complex Quantitative Relationships".

Lecture Slides:

• [Mon] The Display of Multivariate Data, Space and Time
• [Wed, Fri] Space and Time

Week 6: 2/19-2/23

Topics: technique toolbox

Reading:

• [Mon] no reading
• [Wed] no reading
• [Fri] no reading

Lecture Slides:

• [Mon] Space and Time
• [Wed] Space and Time, Graphs and Trees
• [Fri] Graphs and Trees

Week 7: 2/26-3/2

Topics: interaction; prefuse

Reading:

• [Mon] no reading
• [Wed] (wiki page)
  • Stephen Few. "BizViz: The Power of Visual Business Intelligence".
• [Fri] prefuse documentation (particularly SwingBasics and DynamicQueries)

Lecture Slides:

• [Mon, Wed] Interaction

Week 8: 3/5-3/9

Topics: prefuse

Reading:

• [Mon] no reading
• [Wed] prefuse documentation (particularly LinkedVisualizations and Controls)

3/12-3/16

Week 9: 3/19-3/23

Topics: visualization wrapup

Reading:

• [Mon] no reading
• [Wed] prefuse documentation (the LinkedVisualizations section has a new example, with a suggestion for a way to organize your multiple-visualizations program in a somewhat nicer way)

Lecture Slides:

• [Mon, Wed] Visualization Wrapup

Week 10: 3/26-3/30

Topics: introduction to data mining; about input; knowledge representation; classification

Reading:

• [Mon] (wiki page)
  • Witten & Frank, chapter 1 (section 1.5 is optional)
• [Wed] (wiki page)
  • Witten & Frank, chapters 2-3
• [Fri] (wiki page)
  • Witten & Frank, 4.1-4.2

Lecture Slides:

• [Mon] Introduction to Data Mining
• [Wed] Input
• [Fri] Knowledge Representation

Week 11: 4/2-4/6

Topics: basic techniques: classification, association, clustering

Reading:

• [Mon] (wiki page)
  • Witten & Frank, 4.3
• [Wed] (wiki page)
  • Witten & Frank, 4.4
• [Fri] (wiki page)
  • Witten & Frank, 4.5, 4.7-4.8

Lecture Slides:

• [Mon, Wed, Fri] Techniques

Week 12: 4/9-4/13

Topics: basic techniques wrapup; credibility and evaluation; data transformations

Reading:

• [Mon] (wiki page)
  • Witten & Frank, chapter 5: introductory section plus sections 5.1-5.3, 5.5, 5.6 (introductory subsection only), 5.7 (read the introductory subsection, "Cost-Sensitive Classification", and "Cost-Sensitive Learning"; skim the rest of the section)
    The rest of chapter 5 and all sections marked with a gray sidebar are optional.
• [Wed] (wiki page)
  • Witten & Frank, chapter 7: introductory section, 7.1-7.4 except the "Other Discretization Methods" and "Entropy-Based vs. Error-Based Discretization" subsections of 7.2 and the "Robust Regression" subsection of 7.4 + skim section 7.6
    The rest of chapter 7 and all sections marked with a gray sidebar are optional.
• [Fri] no reading

Lecture Slides:

• [Mon] Techniques, Evaluation
• [Wed] Evaluation
• [Fri] Transformations

Week 13: 4/16-4/20

Topics: data mining with Weka

Reading:

• [Mon]
  • Witten & Frank, 10.1-10.2 except the "Do it yourself" and "Using a metalearner" subsections in 10.2
    Read with the idea of getting an overview of what Weka can do and how it is organized, and as documentation (make note of what can be done so you can look it up when you need it).
• [Wed]
  • Witten & Frank, 10.3-10.4 except the "Neural networks" subsection in 10.3, 10.6-10.8
    Read this as documentation - make note of what can be done so you can look it up when you need it.
• [Fri] no reading

Week 14: 4/23-4/27

Topics: data mining with Weka; extensions and applications; social and ethical issues

Reading:

• [Mon] no reading
• [Wed] (wiki page)
  • Witten & Frank, chaper 8
• [Fri] (wiki page)
  • K. Shermach, Data Mining: Where Legality and Ethics Rarely Meet
  • Feingold Introduces Legislation Placing A Moratorium On Data Mining
  • "Data Mining" Is NOT Against Civil Liberties
  • H. MacDonald, What We Don't Know Can Hurt Us

Lecture Slides:

• [Wed] Extensions and Applications
• [Fri] Privacy and Ethics

Week 15: 4/30-5/4

Topics: project demos

5/5-5/8

last updated: --Wed May 2 18:39:52 EDT 2007--
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