CS 519: Scientific Visualization

Fall  2017

M/W      11-12:15 pm,
Room 1310 Digital Computer Lab

University of Illinois at Urbana-Champaign,
Department of Computer Science
Instructor : Eric Shaffer
Office: 2209 Siebel Center
Office Hour: M 2-3pm or by appointment

Book:  Data Visualization: Principles and Practice, Second Edition by Alexandru C. Telea

Piazza: This term we will be using Piazza for class discussion. Rather than emailing questions to the teaching staff, we encourage you to post your questions on Piazza. Find our class page at: piazza.com/illinois/fall2017/cs519/home

Grading: The course grade for the class is broken down among the following items:

Machine Problem 1  10%
Machine Problem 2  10%
Machine Problem 3  10%
Machine Problem 4  10%
Course Project  20%
Exam 1   20%
Exam 2  20%





Machine Problems: There will be 4 machine problems during the semester. Assignments will be announced in class and on Piazza. Homework submission will be done electronically through Compass. The required files and acceptable file formats for submission will be specified in the assignment.

Project: There will also be a course project during the semester. The project can be one of your choosing and should either be the creation of a non-trivial visualization using whatever tools you wish or the implementation of a non-trivial visualization algorithm or data structure. The project will be due on the final day of class. You will need to present your project in class prior to that final submission. You will work in teams, and we will work on teaming up people based on interests.

Exams: There will be two in-class exams. 

Late Homework or Projects:  Machine problems and projects submitted after the due date lose 10% per day. In exceptional circumstances where extension may be reasonable (illness, family emergency etc.) arrangement must be made with the instructor.

Collaboration: You should collaborate on the MPs. You should not copy code verbatim from each other or the web. Obviously the projects are collaborative and the exams  are not.

Software:  There is no official programming language for the class…however the MPs will require the use of specific languages and libraries which which will be described in the assignment.

Other Policies: Do not make class material publicly available. This includes copies of lectures, homework, solutions, handouts, and code provided by us.

Language References and Resources:

Tentative Schedule:

Date Topic Materials Assignments
8/28 Introduction

  • Lecture 1: Introduction [PDF]
  • Visualizing a Black Hole [link]
  • Worksheet 0: Introduction to Visualization [PDF]
    Solution [PDF]

Data Representation


  • Lecture 2: Data in Scientific Visualization [PDF]
  • NCSA Tornado Visualization [link]
  • NCSA Solar Storm Visualization [link]
  • Scattered Data Interpolation by Tao Ju [link]
    Chapter 10 of A Sampler of Useful Computational Tools for Applied Geometry, Computer Graphics, and Image Processing Edited by Daniel Cohen-Or
  • Worksheet 1: Interpolation [PDF]
    Solution [PDF]

  • Read Chapter 4 of Information Visualization: Perception for Design
9/4 Labor Day Holiday: No Class       


  • Lecture 3: Color [PDF]
  • Read Chapter 5 of Data Visualization: Principles and Practice

JavaScript and HTML5


  • Introduction to JavaScript and HTML5 [link]
  • Your tasks [PDF]
9/13 Scalar Data Techniques
  • Lecture 4: Scalar Visualization [PDF]
  • MP 1 Due Sept. 29 at 11:55pm [PDF]

Scalar Data Techniques

  • Lecture 4: Scalar Visualization [PDF]


  • Worksheet 3: Dual Contouring [PDF]
    Solution [PDF]

      From Isosurfaces Geometry, Topology, and Algorithms
      by Rephael Wenger

  • Marching Cubes and Variants[PDF]
  • Dual Contouring [PDF]

Vector Field Visualization

  • Lecture 5: Vector Fields 1 [PDF]
  • Read Chapter 6 of Data Visualization: Principles and Practice
    Section 6.1 through 6.

  • Vector visualization example [link]
  • Numerical Integration Worksheet [PDF]
  • Solution [PDF]
9/25 Vector Field Visualization
  • Lecture 6: Vector Fields 2 [PDF]
  • Read Chapter 6 of Data Visualization: Principles and Practice Section 6.5 through 6.6
  • Flow Visualization Part 1 By Professor Steven Kline [YouTube]
  • MythBusters Non-Newtonian Fluid [YouTube]
9/27 Vector Field Visualization


  • Lecture 7: Vector Fields 3 [PDF]
  • Lecture 8: Vector Field Simplification [PDF]
  • Read Chapter 6 of Data Visualization: Principles and Practice
    Section 6.7 
  • LIC Worksheet [PDF]
  • Solution [PDF]
10/2 Tensor Visualization
  • Lecture 9: Tensor Visualization [PDF]
  • Read Chapter 7 of Data Visualization: Principles and Practice
  • Vector Visualization Worksheet [PDF]
  • Solution [PDF]
10/4 Domain Modeling 
  • Lecture 10:
    Mesh Processing [PDF]
  • MP2 Due Oct 18, 11:55pm [PDF]
  • The Discovery of Gravitational Waves | Nergis Mavalvala [YouTube]
  • Read Chapter 8 of Data Visualization: Principles and Practice
10/9 Exam 1    
10/11 Terrain Visualization


  • Use of LiDAR in the world and data processing with LAStools [link]
  • Mesh Generation Video [link]
10/16 Volume Visualization
  • Lecture 11: Volume Visualization [PDF]


  • Mesh Processing Worksheet [PDF]
  • Solution [PDF]
  • Example Volume Data [VTK]​


10/23 Volume Visualization
  • Lecture 11: Volume Visualization [PDF]
  • Read Chapter 10 of Data Visualization: Principles and Practice
  • Volume Visualization Worksheet [PDF]
  • Solution [PDF] [Page 2 PDF]
10/25 Time Series Data
  • Lecture 12:Time Series [PDF]
  • The TimeViz Browser: A Visual Survey of Visualization Techniques for Time-Oriented Data [link]
  • Time Series Worksheet [PDF]
  • Solution [PDF]
10/30 Information Visualization Overview
  • Lecture 13: Information Visualization [PDF]
  • Chapter 4 Marks and Channels from Visualization Analysis and Design
    by Tamara Munzner [link to UIUC library copy]
  • In-Class Exercise [PDF]
11/1 Table Visualization
  • Lecture 14: Table Visualization [PDF]
  • Read Chapter 11 of Data Visualization: Principles and Practice
  • Chapter 7 Arrange Tables from Visualization Analysis and Design
    by Tamara Munzner [link to UIUC library copy]
11/6 Design Principles
  • Lecture 15: Information Visualization Design [PDF]
  • Tabular Data Worksheet [PDF]
  • Solution [PDF]
11/8 Network Visualization
  • Lecture 16: Graph Visualization [PDF]
  • Chapter 9 Arrange Networks and Trees from
    Visualization Analysis and Design
    by Tamara Munzner [link to UIUC library copy]
  • Squarified TreeMaps [PDF]
  • Graph Drawing by Force-Directed Placement [PDF]
  • Network Visualization Worksheet [PDF]
  • Solution [PDF]

Visualizing Large Networks

  • Lecture 17: Graph Visualization [PDF]
  • MP3 Due Nov 29 at 11:55 pm [PDF]
  • Visual Analysis of Large Graphs: State-of-the-Art and Future Research Challenges. von Landesberger, et al (2011),Computer Graphics Forum[PDF]
  • Network Metric Worksheet [PDF]
  • Solution [PDF]
11/15 Exam 2    
11/20 Fall Break: No Lecture


11/22 Fall Break: No Lecture  


No Lecture
Highlights from IEEE Vis 2017
  • Best Paper IEEE VAST 2017: Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow by Kanit Wongsuphasawat et al [PDF][Video]
  • Best Paper IEEE InfoVis 2017Modeling Color Difference for Visualization Design by Danielle Albers Szafir [PDF] [Slides] [Video]
  • Best Paper IEEE SciVis 2017Globe Browsing: Contextualized Spatio-Temporal Planetary Surface Visualization by Karl Bladin et al [PDF][Video]
12/4 Project Presentations  


12/6 Project Presentations  


12/11 Project Presentations  


12/13 Project Presentations