Schedule

Please note that this schedule is subject to change.

Calendar

Date	Topic	Readings	Assignments
8/28	Introduction	Ch. 1
8/30	Web Programming
9/04	No Class
9/06	Web Programming
9/11	JavaScript
9/13	JavaScript & Data	Ch. 2
9/18	Data
9/20	Tasks	Ch. 3
9/25	D3
9/27	D3
10/02	Marks & Channels	Ch. 5
10/04	Tabular Data	Ch. 7
10/09	Color	Ch. 10
10/11	Color
10/16	Geospatial Data	Ch. 8.1-8.3
10/18	No Class
10/23	Midterm
10/25	Networks	Ch. 9
10/30	Trees
11/01	Design	Ch. 4
11/06	Interaction	Ch. 6
11/08	Multiple Views	Ch. 11
11/13	Filtering & Aggregation	Ch. 12 & 13
11/15	Focus+Context & Data	Ch. 14
11/20	Isosurfacing	Ch. 8.4
11/22	No Class
11/27	Volume Rendering	Ch. 8.5
11/29	Vector Visualization
12/04	Project Presentations
12/06	Project Presentations
12/11	Final Exam (12:00pm)

Lectures

(08/28) Introduction

• Slides
• Reading: Ch. 1

(08/30) Web Programming

• Slides

(09/06) Web Programming

• Slides
• Observable Notebook (Use NIU Email for Team Access)

(09/11) JavaScript

• Slides
• Observable Notebook (Use NIU Email for Team Access)

(09/13) JavaScript & Data

• Slides
• Reading: Ch. 2
• Observable Notebook (Use NIU Email for Team Access)

(09/18) Tasks

• Slides
• Reading: Ch. 3

(09/20) D3

• Slides
• Observable Notebook (Use NIU Email for Team Access)

(09/25) D3

• Slides
• Observable Notebook (Use NIU Email for Team Access)

(09/27) D3

• Slides

(10/02) Marks & Channels

• Slides
• Reading:
  • Ch. 5
  • Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods, W. S. Cleveland and R. McGill, 1984.
  • Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design, J. Heer and M. Bostock, 2010.
• Example (Produce):
  • Tableau
  • Observable Plot (Use NIU Email for Team Access)

(10/04) Tabular Data

• Slides
• Reading: Ch. 7

(10/09) Color

• Slides
• Reading:
  • Ch. 10
  • Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts, D. Skau and R. Kosara, 2016.
  • Judgment Error in Pie Chart Variations, R. Kosara and D. Skau, 2016.
  • Blog: An Illustrated Tour of the Pie Chart Study Results
  • Modeling Color Difference for Visualization Design, D. Albers Szafir, 2017.

(10/11) Color

• Slides
• Reading:
  • Evaluating the Impact of Binning 2D Scalar Fields, L. Padilla et al., 2016.
  • Turbo, An Improved Rainbow Colormap for Visualization, A. Mikhailov, 2019. [Stevens’ Critique]
  • Your Friendly Guide to Colors in Data Visualization, L. C. Rost
  • How to pick more beautiful colors for your data visualizations, L. C. Rost
  • Value-Suppressing Uncertainty Palettes, M. Correll et al., 2018.

(10/16) Geospatial Data

• Slides
• Reading:
  • Ch. 8.1-8.3
• Observable Notebook (Use NIU Email for Team Access)

(10/25) Networks

• Slides
• Reading: Ch. 9
  • Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data, D. Holten, 2006.

(10/30) Trees

• Slides
• Reading:
  • Cushion Treemaps: Visualization of Hierarchical Information, J. J. van Wijk and H. van de Wetering, 1999.
  • Squarified Treemaps, M. Bruls et al., 1999.
• Observable Notebook

(11/01) Design

• Slides
• Reading:
  • Ch. 4
  • Sketching Designs Using the Five Design-Sheet Methodology, J. Roberts et al., 2016.

(11/06) Interaction

• Slides
• Reading:
  • Ch. 6
  • Animated Transitions in Statistical Data Graphics, J. Heer and G. G. Robertson, 2007.
  • imMens: Real-time Visual Querying of Big Data, Z. Liu et al., 2013.

(11/08) Multiple Views

• Slides
• Reading:
  • Ch. 11
  • Exploring the Design Space of Composite Visualization, W. Javed and N. Elmqvist, 2012.

(11/13) Filtering

• Slides
• Observable Notebook (Use NIU Email for Team Access)
• Reading: Ch. 12 & 13

(11/15) Aggregation & Focus+Context

• Slides
• Reading:
  • Ch. 14
  • Probing Projections: Interaction Techniques for Interpreting Arrangements and Errors of Dimensionality Reductions, J. Stahnke et al., 2015

(11/20) Isosurfacing

• Slides
• Reading: Ch. 8.4

(11/27) Volume Rendering

• Slides
• Reading: Ch. 8.5

(11/29) Vector Visualization

• Slides