California State University Stanislaus

CS 3520 Section 1: Data Visualization

Spring 2025

CS 3520: MWF   10:00 am - 10:50 am,  DBH 101,  Dr. Melanie Martin

[Basic Information]         [Announcements]         [Calendar]         [Links]        

Welcome to CS 3520, Data Visualization

This course satisfies the General Education Upper-division Area B requirement. It can also be used as a CS elective, if you have not already taken CS 3500, CS 3550, or CS 4010.

Course Description:

The purpose of this class is to provide students with background and training in basic programming and computational methods to gain the skills necessary to work with a wide variety of data sets. In this course, students will learn how to use tools to visualize data and learn to understand the theory, practice and ethics of data collection and use. No prior programming experience is expected.

 

Student Learning Outcomes:

  1. Students will understand the basic principles behind effective data visualization.
  2. Students will be able to create a wide range of plots in an appropriate programming environment, such as R.
  3. Students will be able to refine plots for effective presentation.
  4. Students will be able to find data and work in a team to present and visualize the data.
  5. Students will explain the issues surrounding the collection and representation of data.

General Education Learning Outcomes:

Announcements and Upcoming Events

1/29/25          

Welcome to CS 3250!                        



Basic Information

Required Textbook: Kieran Healy, Data Visualization: A Practical Introduction (Princeton: Princeton University Press, 2019), http://socviz.co/. A draft version is freely-available online.

Other books we will use:


Alberto Cairo, The Truthful Art: Data, Charts, and Maps for Communication (Berkeley, California: New Riders, 2016). A free eBook version is available through the Stan State library through O’Reilly’s Higher Education database.


 Claus E. Wilke, Fundamentals of Data Visualization (Sebastopol, California: O’Reilly Media, 2018), https://serialmentor.com/dataviz/.


Recommended: It is recommended that students have a laptop (or tablet) that they can bring to class to work on in-class assignments using Excel and R.

Prerequisites/Corequisites: N/A

Instructor: Dr. Melanie Martin                                  Office: Demergasso-Bava Hall 278
                                                                                               

Email: mmartin@csustan.edu                                 Office Phone: (209) 667-3787

Web Page: www.cs.csustan.edu/~mmartin

Office Hours:

Please note that I may sometime have to reschedule or cancel office hours. If I do I will post in the Announcements and/or send email.
For Zoom Office Hours - Meeting URL: https://csustan.zoom.us/j/88404918801

Monday
 3-3:30 pm
 DBH 278
Tuesday
 3-4 pm zoom
Wednesday
 3:30-5 pm DBH 278

and by appointment

Best way to contact Dr. Martin:  Email mmartin@csustan.edu  Please put "CS 3520" in the subject line of the email.

Warning: I reserve the right to make changes to the syllabus at any time during the term by announcing them in class and on my web page.


Health and Safety

This course is designed to be an in-person: some days may be online, most of those will be synchronous. Assume class is in-person unless I announce otherwise.

Organization:

IT IS VERY IMPORTANT TO ATTEND CLASS. I plan to make it possible to attend synchronous in a virtually manner. Class participation is part of your grade (described below) and the structure of class is additive - meaning we will constantly be building on concepts through in-class lectures, examples, and practical applications. The majority of your grades in this course will be practical in nature and it will be important to regularly practice the applications of skills we go over in class.

 

Grading:

Grading for this course will consist of assignments, participation, and a final project and the presentation of the final project. All assignments and quizzes will be on a 0-10 or 0-20 point scale and project grades may be on a 0-100 point scale.

 

Assignments (50%): There will likely be approximately 6 programming assignments although I reserve the right to change this depending on how the class is proceeding. You must turn in a working version of all assignments to pass the course. In addition there will be many in-class assignment involving discussion and reflection and outside of class reading/viewing and reflection that will be included in the section.

 

Participation and Quizzes (10%):

Simply put, this is a grade based largely on class attendance. Attend class and make proper use of class time and you will get this. There may be short quizzes to ensure that students are keeping pace with, and understanding the material presented in class.

 

Final Project (40%): The final project will allow individual or groups of students to work in more depth on a visualization problem.

 

Class Conduct:

Please be respectful and professional in how you interact with both myself and your classmates. I plan on acting the same way with you. No food or beverage allowed in the computer lab.

Academic Honesty: The work you do for this course will be your own, unless otherwise specified. You are not to submit other people's work or the work of an AI and represent it as your own. I consider academic honesty to be at the core of the University's activities in education and research. Academic honesty is expected at all times in this course. Cheating is an attack on the efforts of myself and fellow students and, above all, on the cheater's integrity. Those caught cheating will be dealt with to the full extent allowed under University policy. If you have questions, please ask!

Collaboration and Teamwork:  Students are encouraged to co-operate on assignments by discussing the problems. That does not mean labor division in terms of problem solutions. All problems for all assignments have to be done by the very student who is submitting the assignment. Copying someone else's work OR allowing someone to copy your work are prohibited. All discussions and other aids used must be explicitly and properly acknowledged. For instance (examples based on Vadim Bulitko's http://www.cs.ualberta.ca/~bulitko/W04):

"I discussed problem 3.43 with my classmates K. Black and P. Posey. On problem 3.49 I received an office-hour consultation from my instructor R. Altman.  Additionally I used sources [1] and [2] for problem 3.78.

[1]. A.Jolie. "Fast Numeric Methods for Curvature Approximation",  Journal of Geeky Gamers, volume 36, issue C, June 2001.

[2] F.Oz. "On Using the Force as a Theorem Proving Technique", Jedi Archives, volume 666, number 34, May 2002."

There will be NO collaboration allowed on quizzes and final exam. Any unacknowledged aid (e.g., copying from other students, copying from external sources, or elsewhere) constitutes a case of plagiarism. 

Any use of AI, must be cited and the prompt included to avoid plagiarism. In addition, anything produces by an AI must be fact checked and the fact checking documented.

Cell Phone Policy: During class time, your cell phone (including headsets) must be turned off and out of sight. Any use of a cell phone during class may result in confiscation of the phone until that day's class has ended or your removal from the class for that day. If you attempt to use your cell phone or leave it on during an exam, you will be considered to have finished your test, and I will collect your exam at that time.  Exceptions may be made only if you discuss your situation with me prior to the start of that day's class, in this case, your cell phone must be set to vibrate/silence.

University Recording Policy: Audio or video recording (or any other form of recording) of classes is not permitted unless expressly allowed by the faculty member as indicated in the course syllabus or as a special accommodation for students who are currently registered with the Disability Resource Services Program and are approved for this accommodation. Recordings allowed as special accommodations are for the personal use of the DRS-approved student, and may only be distributed to other persons who have been approved by the DRS program. Faculty may require the student sign an Audio/Video Recording Agreement, which they may keep for their records.

University Disability Services:  CSU Stanislaus respects all forms of diversity. By university commitment and by law, students with disabilities are entitled to participate in academic activities and to be tested in a manner that accurately assesses their knowledge and skills. They also may qualify for reasonable accommodations that ensure equal access to lectures, labs, films, and other class-related activities.   Please see the instructor if you need accommodations for a registered disability.  Students can contact the Disability Resource Services office for additional information.  The Disability Resource Services website can be accessed at http://www.csustan.edu/DRS/ Phone: (209) 667-3159

Important dates:

(See Schedule of Courses or Academic Calendar)

Last day to add a class:                     

February 24;

Last day to drop: 
February 24;
Last day to change grade options (CR/NC): May 18 at 5 pm;

No classes

March 31, April 1-4.