CSE5544 – Introduction to Data Visualization

CSE5544 is offered under the auspices of the Department of Computer Science and Engineering, The Ohio State University. It is a service course and will serve all those interested and enthusiastic about data visualization and data analytics.


Course Description. This course will provide a basic introduction to the science and the underlying technology of visual analytics.  The following topics will be studied –  the role of perception in visualization, the importance of good design practices in visual analytics, the construction of interactive tools for data and information visualization, and the application of visualization techniques on collected/surveyed data from transactional and behavioral sciences; measured data from medical and biological sciences; and simulated data from physical sciences and engineering. In particular, we will consider methods for visualizing categorical and nominal data manifest in databases, techniques for scalar and vector data, algorithms to visualize trees, and graphs and custom workflows for various application domains.   Case studies and examples will be considered giving the course an application-focus and interdisciplinary flavor. Hands-on programming experience, the design of interfaces, and user studies and evaluations, will be stressed throughout the class and thereby providing the students a practical emphasis. Of special interest to many will be the use of popular platforms including Tableau, Processing, D3, etc.


Course Contents: Interactivity, Visual Mapping, Data/Information Visualization, Application-specific visualization


The Highlights: User Studies, Design, Tableau, D3.js, Processing, Application-domain user interface design

Prerequisites: Coursework in Numerical Methods/Linear Algebra/Statistics, Or Computer Graphics/Multimedia/Animation, Or Permission of Instructor

Text Books:

1.    Visualization Analysis and Design, Tamara Munzner, CRC Press, 2014

2.    Interactive Data Visualization for the Web, Scott Murray, O’Reilly, 2013 

Other Materials

1.    Data Analysis with Open Source Tools, Philipp K. Janert, O’Reilly 2010

2.    Think Stats, Allen B. Downey, O’Reilly, 2014


Instructor: Raghu Machiraju, Professor - Departments of Computer Science and Engineering and Bioinformatics, Faculty-in-Residence, The Ohio State University


Grading Assistant: TBA, Department of Computer Science and Engineering


Time: TR 11:10 AM -12:30 PM: Bolz BO0314

Office Hours:   Instructor - TR 1:00-2:00 PM, DL 779. Please contact me if needed at machiraju dot 1 at osu dot edu.

Grader, Chaitanya Kulkarni - Hours:  WF 3:00-5:00 PM (tentative), Dreese Graduate Lounge (tentative)

Contact:  kulkarni dot 132 at buckeyemail dot osu dot edu.


Grade Distribution: Laboratory Assignments: 50%, Take Home Midterm: 20%, Final Project: 30%

Class Help/Watering Hole: Piazza - https://piazza.com/osu/autumn2016/cse5544/home

The Final Project Deadline: Monday May 2, 201, 10-11:45 AM.

The Schedule & Lectures

Week 1


Introduction (pdf)
[Munzner Ch, 1]


Design Principles (pdf)

First Week

Week 2


Design Principles (pdf)


Tableau – Guest Lecture: Robert Kosara, Tableau


Week 3


Lab1+Data Types,(pdf)
[Munzner Ch. 2]


Data Types (pdf)
[Munzner Ch. 2]


Week 4


Tasks (pdf)

[Munzner Ch. 3]


Hao Ding’s D3 Tutorial –

2/2 - Lab 1 Due, D3
[d3 paper]
[D3 demo code]

Week 5


D3 Again, Design (pdf) 
R - [Munzner Ch. 4]

Very Useful Tutorial


Visual Encoding Principles  (pdf) 

[Munzner Ch. 5]


Week 6


Peer Review of Lab 1,

Code Review of Lab2


Arrange Tables (pdf) 

[Munzner Ch. 7]


Week 7


Arrange Tables (pdf) 

[Munzner Ch. 7] 


Networks/Trees (pdf) 

 [Munzner Ch. 9]

2/25 – Lab 2 due

Week 8


Networks/Trees (pdf) 


Networks/Trees (pdf) 

Working with graphs, D3

Week 9


Midterm Review – Designing Graphical Layouts Automatically (The Midterm)


Using D3 to make Graph Layouts


3/11 – Midterm Due

Week 10


Spring Break


Spring Break

Head South

Week 11


Lab2 Peer Review/Lab3 Code Review


Maps (pdf)
D3 for Maps (

3/28  Lab3 Due

Week 12


Dimensionality Reduction (pdf)


Interaction  (pdf)


Week 13


Sci Visualization-I (pdf)


Sci Visualization-II (pdf)

4/5, Lab 4 due

Week 14


Sci Visualization/Guest


Sci Visualization

Project Proposal

Week 15


Project Presentations


Sci Viz/Project Presentations

Last Week



1.    Lab 1: Due: 2/2 : Visualizations with Tableau and evaluate them. Details to be available soon.

2.    Lab 2: Due 2/23 : Build a user interface in D3 which displays word tags learnt from a text document. More details to follow.

3.    Lab 3: Due Part A - 3/11; Part B : 3/28 Build a user interface in D3 which allows the visual layout of graphs from an application of your choice.

4.    Lab 4: Due 4/11:  Build a user interface in D3 that facilitates the correlation of data with spatial maps.



Due: Friday, March 11, midnight.

The midterm is all about automating the visualization of 2D plots and visualizing large graphs. Given some specifications and data, could you automatically generate a graph. You will note that this could be done in some contexts. Similarly, are there are really ways to avoid hairballs. You will be asked to review a method to answer that question. Find the full  exam here.


Final Project:

1.    Form a group of 3 and choose a project.

2.    Due Midnight May 2, 2016 on Carmen.

3. If you choose to demo the project in person, please meet me on May 3 or May 4 (times to be posted on Piazaa).

4. Present a project Proposal on Thursday, May 21, 2016.

5.    Choose one of the projects below:

1.    Resume Builder

2.    Goodwill Stores Visualizers

3.    Cooking Recipe Visualizers

4.   Anatomy Image Explorer

5.   Whole Cell Visualizer


1.    Tableau's data visualization software is provided through the Tableau for Teaching program. Access details follow through piazza and e-mail.

2.    A free alternative to Tableau is Lyra. You are welcome to use this instead, but we will not provide any support/help.

3.    An expansive resource for data http://keshif.me/. Keshif can be used a validation tool.

Reading Lists

Week 1

1.       Design Study Methodology: Reflections from the Trenches and the Stacks. Michael Sedlmair, Miriah Meyer, and Tamara Munzner. IEEE Trans. Visualization and Computer Graphics (Proc. InfoVis 2012), 18(12):2431-2440, 2012.

2.       A Tour through the Visualization Zoo. Jeffrey Heer, Michael Bostock, Vadim Ogievetsky. Communications of the ACM, 53(6), pp. 59-67, Jun 2010.

3.       The Value of Visualization.Jarke van Wijk. Proceedings of the IEEE Visualization Conference, pp. 79-86, 2005.

4.     Pitfalls of writing a Vis Paper, Tamara Munzner.

5.     The Nature of External Representations in Problem Solving. Jiajie Zhang. Cognitive Science 21:2 (1997), 179-217.

6.       A Representational Analysis of Numeration Systems. Jiajie Zhang and Donald A. Norman. Cognition 57 (1995), 271-295.

7.       Why a Diagram Is (Sometimes) Worth Ten Thousand Words.. Jill H. Larkin and Herbert A. Simon. Cognitive Science 11:1 (1987), 65-99.

8.       Graphs in Statistical Analysis. F.J. Anscombe. American Statistician 27 (1973), 17-21.

9.       Current approaches to change blindness Daniel J. Simons. Visual Cognition 7, 1/2/3 (2000), 1-15.

10.    Semiology of Graphics, Jacques Bertin, Gauthier-Villars 1967, EHESS 1998

Week 2

  1. Design Principles for Visual Communication. Maneesh Agrawala, Wilmot Li, Floraine Berthouzoz. Communications of the ACM, 54(4), pp. 60-69, Apr 2011.
  2. Design of data figures. Bang Wong. Nature Methods 7, pp. 665, Sept 2010.


Week 3

1.     1.     On the Theory of Scales of Measurement. S. S. Stevens. Science, 103(2684), pp. 677-680, June 1946.


Week 4-5

1.     D3, HTML, CSS resources

1.     University of Arizona – Carlos Scheidegger

1.     HTML, CSS

2.     Javascript Basics

3.     SVG Tutorial – READ THIS !

4.     Even More D3

2.     University of ViennaTorsten Moeller, Tom Torsney-Weir

3.     University of Utah – Alex Lex

1.     HTML, CSS

2.     JavaScript


For Viewing Pleasure

Week 1

1.    Stephen Few - http://www.perceptualedge.com/

2.    Tufte – http://www.edwardtufte.com/tufte/