CS-GY 6313 Information Visualization Fall 2025 - Detailed Schedule

CS-GY 6313 Information Visualization Fall 2025 - Detailed Schedule

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Detailed Schedule

Week 1 (Sept 5) - Introduction and Evaluation

Learning Objectives: Understand what visualization is, when to use it, and how to evaluate effectiveness

Lecture: Week 1 - Course Introduction & Syllabus

  • Course overview and expectations
  • What is information visualization?
  • Visualization taxonomy and design space
  • Evaluation frameworks and criteria
  • Introduction to tools landscape (Vega-Lite, D3, Tableau, etc.)

Required Readings:

Optional Reading:

Lab: Week 1 Lab - Introduction to Observable and Vega-Lite

  • Setup Observable accounts
  • Create first basic charts in Vega-Lite
  • Explore provided datasets
  • Chart gallery exploration

Assignment: Exercise 1 - Visualization critique and basic Vega-Lite charts (due Sept 11)

Week 2 (Sept 12) - Analytical Questions and Data Transformation

Learning Objectives: Transform questions into visual queries; understand data transformation pipelines

Lecture:

  • From questions to visual mappings
  • Data types and structures
  • Data transformation operations (filter, aggregate, derive)
  • Query-based visualization systems
  • Introduction to Observable notebooks

Required Readings:

Optional Reading:

Lab:

  • Vega-Lite data transformations
  • Working with real datasets in Observable
  • Data aggregation and filtering
  • Creating derived fields

Assignment: Exercise 2 - Data questions and transformations using Vega-Lite (due Sept 18)

Week 3 (Sept 19) - Fundamental Graphs and Visual Encoding

Learning Objectives: Master basic chart types and understand when to use each; apply grammar of graphics

Lecture:

  • Chart types and their purposes
  • Marks and channels theory
  • Grammar of graphics principles
  • Comparison strategies
  • When to use different chart types

Required Readings:

  • Chapter 1: Graphical Excellence, in The Visual Display of Quantitative Information. Tufte.
  • Chapter 2: Graphical Integrity, in The Visual Display of Quantitative Information. Tufte.
  • Multi-View Composition (Observable)

Optional Reading:

Lab:

  • Creating multiple chart types in Vega-Lite
  • Exploring encoding alternatives for same data
  • Small multiples and faceting
  • Combining multiple views

Assignment: Exercise 3 - Chart design and encoding alternatives (due Sept 25)

Week 4 (Sept 26) - Deceptive Visualization and Design Ethics

Learning Objectives: Identify misleading visualizations; understand ethical design principles; recognize cognitive biases

Lecture:

  • Types of misleading visualizations
  • Intentional vs. unintentional deception
  • Cognitive biases in visualization interpretation
  • Ethical responsibilities of designers
  • Case studies of deceptive visualizations in media

Required Readings:

Optional Readings:

Lab:

  • Analyze deceptive visualization examples
  • Create misleading and honest versions of same data
  • Redesign problematic visualizations
  • Discussion and critique session

Assignment: Exercise 4 - Design misleading vs. honest versions of same data (due Oct 2)

Week 5 (Oct 3) - Visual Perception and D3 Foundations

Learning Objectives: Understand human visual perception principles; begin D3 programming

Lecture:

  • Pre-attentive processing and visual attention
  • Gestalt principles in visualization
  • Color perception and accessibility
  • Introduction to D3.js: concepts and architecture
  • DOM manipulation basics

Required Readings:

Optional Reading:

Lab:

  • First D3 programming session
  • DOM manipulation exercises
  • Data binding concepts
  • Create simple bar chart in D3

Assignment: Exercise 5 - Perception-based design decisions + D3 implementation (due Oct 9)

Week 6 (Oct 10) - Color and D3 Scales

Learning Objectives: Master color theory for visualization; implement D3 scales and color schemes

Lecture:

  • Color theory fundamentals
  • Perceptual color spaces (RGB, HSL, LAB)
  • Colorblindness and accessibility
  • Color palette design strategies
  • D3 scales: linear, ordinal, time, color

Required Readings:

Optional Readings:

Lab:

  • D3 scales implementation
  • Color scheme creation and testing
  • Accessibility testing tools
  • Apply color theory to previous D3 examples

Assignment: Exercise 6 - Color design with D3 scales (due Oct 16)

Fall Break (Oct 11-13) - NO CLASS

Week 7 (Oct 17) - Interaction and Animation

Learning Objectives: Design effective interactions; implement smooth animations and transitions

Lecture:

  • Interaction design principles
  • Types of interaction (selection, filtering, details-on-demand)
  • Animation theory and when to use it
  • Easing functions and timing
  • Coordinated multiple views

Required Readings:

Optional Readings:

Lab:

  • D3 event handling (hover, click, brush)
  • Creating smooth transitions and animations
  • Implementing tooltip and details-on-demand
  • Coordinating multiple views

Assignment: Exercise 7 - Interactive visualization with smooth transitions (due Oct 23)

Week 8 (Oct 24) - Geographic and Urban Visualization I

Learning Objectives: Understand map projections and geographic data; create effective choropleth and point maps

Lecture:

  • Map projections and their trade-offs
  • Geographic data formats (GeoJSON, TopoJSON, Shapefiles)
  • Choropleth map design principles
  • Point mapping and density visualization
  • Multi-scale geographic visualization

Required Readings:

Optional Readings:

Lab:

  • D3 geo projection setup
  • Loading and displaying maps
  • Creating choropleth maps with real data
  • Point mapping exercises

Assignment: Mini-project 1 begins - Geographic visualization (due Nov 6)

Week 9 (Oct 31) - Temporal Data and Urban Dynamics

Learning Objectives: Design effective time series visualizations; understand temporal patterns in urban data

Lecture:

  • Time series design principles
  • Temporal data types and structures
  • Animation vs. static temporal representation
  • Seasonal and cyclical patterns
  • Urban temporal dynamics

Required Readings:

Optional Readings:

Lab:

  • D3 time scales and axes
  • Line charts and area charts for time series
  • Brushing and zooming for temporal data
  • Small multiples for temporal comparison

Assignment: Mini-project 2 begins - Temporal visualization (due Nov 20)

Week 10 (Nov 7) - Uncertainty and Data Quality

Learning Objectives: Represent uncertainty visually; assess and communicate data quality issues

Lecture:

  • Types of uncertainty in data
  • Visual encoding of uncertainty
  • Error bars and confidence intervals
  • Alternative uncertainty representations
  • Data quality assessment and communication

Required Readings:

Optional Reading:

Lab:

  • Implementing uncertainty visualizations in D3
  • Confidence intervals and error representations
  • Alternative uncertainty encodings
  • User testing uncertainty representations

Assignment: Continue Mini-project 2 + Exercise 8 - Uncertainty visualization (due Nov 13)

Week 11 (Nov 14) - Network Data and Urban Systems

Learning Objectives: Understand network visualization techniques; apply to urban infrastructure and social systems

Lecture:

  • Network data structures and properties
  • Node-link diagrams and layout algorithms
  • Matrix representations of networks
  • Hierarchical and multilevel networks
  • Urban networks (transportation, social, infrastructure)

Required Readings:

Optional Reading:

Lab:

  • D3 force simulation setup
  • Creating node-link diagrams
  • Network layout algorithms
  • Interactive network exploration

Assignment: Mini-project 3 begins - Network visualization (due Dec 4)

Week 12 (Nov 21) - Scalability and Performance

Learning Objectives: Handle large datasets; optimize visualization performance; understand progressive loading

Lecture:

  • Challenges of large dataset visualization
  • Data aggregation and sampling strategies
  • Progressive loading and level-of-detail
  • Performance optimization techniques
  • Introduction to WebGL for visualization

Required Readings:

Optional Readings:

Lab:

  • Data aggregation techniques
  • Performance profiling and optimization
  • Canvas vs SVG performance comparison
  • Introduction to visualization with large datasets

Assignment: Continue Mini-project 3 + optimization exercises (due Nov 25)

Make-up Class (Nov 26 - Wednesday) - Geographic and Urban Visualization II

Learning Objectives: Advanced geographic techniques; intensive project development time

Extended Workshop (2.5 hours with breaks):

  • Advanced D3 geo techniques
  • Multi-scale mapping strategies
  • Spatial analysis and visualization
  • Working with urban datasets
  • Intensive hands-on work on Mini-project 1
  • Individual guidance and troubleshooting

Assignment: Complete any outstanding work on Mini-project 1

Week 13 (Nov 28) - NO CLASS (Thanksgiving)

Assignment: Complete Mini-project 3 and prepare group project presentations

Week 14 (Dec 5) - Advanced Topics and Project Presentations I

Learning Objectives: Explore emerging trends; present and critique visualization projects

Lecture (45 min):

  • Emerging trends in visualization
  • AI and machine learning visualization
  • Virtual and augmented reality applications
  • Future directions and career paths

Presentations:

  • Group project presentations (first half of teams)
  • Peer feedback and discussion
  • Q&A and critique sessions

Assignment: Prepare final presentations and project documentation

Week 15 (Dec 12) - Project Presentations II and Course Wrap-up

Learning Objectives: Complete project presentations; reflect on learning; plan continued development

Presentations:

  • Final group project presentations (second half)
  • Peer feedback and evaluation
  • Class discussion of projects and techniques

Wrap-up:

  • Course reflection and key takeaways
  • Resources for continued learning
  • Career advice and next steps
  • Course evaluations