CIS/STA 4170 – Sample course syllabus

Title Data Visualization
Description This course examines how to transform data into visual representations so that decision makers can effectively use interactive visualization for analytical reasoning. Topics covered in this course include 1) analytical reasoning techniques, 2) visual representations and interaction techniques, 3) data representation and transformation, and 4) techniques to support production, presentation and dissemination of the results. This course will blend various theoretical and applied technical concepts of visual analytics.
Prerequisites CIS 3100 or CIS 3120
Learning Goals At the completion of the course, students will be able to:

  • Apply the major concepts in visualization design
  • Apply perception and cognition principles in visualization
  • Transform large datasets for visual displays using various representation techniques
  • Critique various visualization representation and interaction techniques

 

Grades
Activity Weight
Individual assignments 25%
Group project report and presentation 25%
Midterm exam 20%
Final exam 20%
Class participation 10%
Textbooks

 

Topics
  • Course introduction
  • General concepts
    • Big Data
    • History of visualization
    • Visualization process
  • Foundations and characteristics of data
    • Types of data
    • Data preprocessing
  • Visual mapping and perception
    • Physiology
    • Perceptual processing
    • Perception in visualization and metrics
  • Visualization foundations
    • Theory of visualization
    • Visualization taxonomy
    • Visualization DOs and DON’Ts
  • Data visualization for the web (D3.js)
    • Introducing D3 and Technology fundamentals (HTML, DOM, CSS, JS, SVG)
    • Binding data
    • Drawing with data
  • Visualization techniques for Multivariate data and Trees and graphs
    • Techniques for point, line, and area data
    • Displaying hierarchical structures
    • Displaying arbitrary graphs/networks
  • Data visualization for the web (D3.js)
    • Scales
    • Axes
    • Updates, Transitions, and Motion
  • Visualization techniques for Spatial and Geospatial data
    • One, Two, Three – dimensional data
    • Visualization of point, line, area data
  • Data visualization for the web (D3.js)
    • Interactivity
    • Layouts
    • Geomapping
  • Designing effective visualizations
  • Comparing and evaluating visualization techniques
  • Project presentations
  • Project presentations
  • Visualization systems
  • Research directions in visualization
  • Final exam review

 

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