CS765 Web Page for 2026 on CS765 Data Visualization 2026

Welcome: What is Vis

Sun, 30 Aug 2026 23:50:02 -0500

A short introduction (2 days over two week) to the topic and the class. We introduce a broad definition of visualizations as solutions to user data tasks and consider how they can be effective at this. We’ll use the basic notion of “what does a visualization make easy to see” to develop intuitions about what makes visualizations effective.

Module 1: Building Blocks

Sun, 30 Aug 2026 23:51:49 -0500

We will look at how we can consider visualizations in terms of building blocks including data and task abstractions and visual encodings. We will see how this allows designing and analyzing visualizations. We will practice design process (including critique). Students will begin to design and analyze visualizations (pen-and-paper).

Module 2: Methodology: Making and Using Visualizations

Sun, 30 Aug 2026 23:51:51 -0500

We will look at strategies for implementing (creating) visualizations and how visualization can be used for exploring data (in addition to communicating stories with it).

Module 3: Methodology: Making and Using Visualizations

Sun, 30 Aug 2026 23:51:53 -0500

We will be more explicit in how we evaluate visualizations and visualization research. We will provide more formal approaches to considering aspects of design and analysis. Students will create and critique visualizations.

We will explore the design, perceptual, cognitive, and data foundations in more depth. We will examine how the science can influence design and practice. Students will apply these ideas to analyze data and create visualizations.

Module 4: Standard (Hard) Problems

Sun, 30 Aug 2026 23:51:56 -0500

We will look at some standard “hard problems” that come up including hard data properties (e.g., uncertainty), data types (e.g., networks, high-dimensional records), and applications. We will look at some of the standard approaches to address these problems. The design exercises will give more practice at creating and critiquing visualizations.

Module 5: Wrap Up

Sun, 30 Aug 2026 23:52:00 -0500

The last week of class.

The Week in Vis: Week 4 (Sep 21-25)

Fri, 18 Sep 2026 14:11:00 -0500

This week we’ll continue learning about the building blocks of visualization and start applying them to design. We’ll make use of what you’ve read about in the first week: we’ll practice critique to learn from visualizations, and we’ll start putting encodings, layouts and transformations together to make visualizations. This week, we’ll also have our first design warmup which will give you a chance to redesign some visualizations.

A Tale of Two Data Sets...

Wed, 16 Sep 2026 09:51:49 -0500

In modules 1, 2, and 3, we will work with two different data sets. This page will give you some information about them. We will use a dataset of life expectancies and a data set of census information.

Design Exercise 1: Sketching Solutions to Real Data Problems

Tue, 15 Sep 2026 20:31:46 -0500

For Design Exercise 1, you will sketch ideas for designs for visualization problems using two sample data sets. Later in the semester, you will use tools (or programs) to make real visualizations. For this assignment we want you to sketch. The goal is for you to think of how visualization designs can answer questions, and to practice sketching to explore designs.

Design Warmup 1: Re-Design (Terrible Vis)

Mon, 14 Sep 2026 18:04:27 -0500

For this Design Warmup, you will critique and redesign (by sketching) some visualizations from an online article. Read the whole assignment first. The goal is to give you practice at critiquing.

Important: for this design exercise you should sketch. This means drawing things by hand. You should not write programs to make visualizations. If you want to draw using a tablet or drawing program, that’s OK - but the spirit of the assignment is for you to sketch on paper (and submit a picture of what you’ve drawn).

The Week in Vis: Week 3 (Sep 14-18)

Fri, 11 Sep 2026 09:21:53 -0500

This week we’ll finally be on a regular schedule… Monday and Wednesday classes, a first week of a three week module (with usually 1st week of module stuff, …). Topic-wise, we’ll begin a module on building blocks: the basic elements that we use to build and analyze visualizations.

The Week in Vis: Week 2 (Sep 8-11)

Mon, 07 Sep 2026 17:20:58 -0500

This is the first of our weekly posts to remind you about what is going on in class this week.

Sample Assignments

Tue, 01 Sep 2026 13:59:44 -0500

The following are some historic examples of assignments, intended to give you some context for the grading scheme. Note that none of these are very long, but they all show different degrees of connection to the readings (and in the case of the Seek and Find examples, to the visualizations). We do not take formatting or (minor) spelling/grammar errors into account when grading.

Since grades for assignments are assigned based on overall quality across multiple answers, these examples are only provided to show expectations.

Readings

Sat, 29 Aug 2026 10:25:07 -0500

Each module will have required readings in the first two weeks. The first week will have backbone and core readings. The second week will have advanced and experientialmodern and historic readings. Modules will also suggest optional readings.

Parts of Class and Rubrics

Sat, 29 Aug 2026 07:58:53 -0500

This class has many components (assignment types). There are Lectures, In Class Activities, Reading Surveys, Content Surveys, Anonymous Surveys, Seek and Finds, Design Warmups, and Design Exercises.

Calendar

Fri, 28 Aug 2026 10:42:25 -0500

Week	Monday	Wednesday	Friday
Welcome: What is Vis?
1 Reading 0-1		Sep 2 Lecture:	Sep 4 Reading Survey 0: Introduction Assignment: None
2 Reading 0-2	Sep 7 Lecture:	Sep 9 Lecture:	Sep 11 Content Survey 0: Experiential Readings Seek and Find 0: Bring a Visualization Video Experiment 0
Module 1: Building Blocks
3 Reading 1-1	Sep 14 Lecture:	Sep 16 Lecture:	Sep 18 Reading Survey 1: Building Blocks Seek and Find 1: Data, Tasks, Encodings
4 Reading 1-2	Sep 21 Lecture:	Sep 23 Lecture:	Sep 25 Content Survey 1: Building Blocks Design Warmup 1: Ask Questions, Sketch Answers
5	Sep 28 Lecture:	Sep 30 Lecture:	Oct 2 Anonymous Survey 1: Attitudes and Preferences Design Exercise 1: Sketches and Questions
Module 2: Methodology: Making and Using Visualizations
6 Reading 2-1	Oct 5 Lecture:	Oct 7 Lecture:	Oct 9 Reading Survey 2: Implementation and Methodology Seek and Find 2: Too much stuff
7 Reading 2-2	Oct 12 Lecture:	Oct 14 Lecture:	Oct 16 Content Survey 2: Implementation and Methodology Design Warmup 2: Make my visualizations
8	Oct 19 Lecture:	Oct 21 Lecture:	Oct 23 Anonymous Survey 2: How is this working? Design Exercise 2: Life Expectancy (stories)
Module 3: Principles and Formalism
9 Reading 3-1	Oct 26 Lecture:	Oct 28 Lecture:	Oct 30 Reading Survey 3: Principles and Formalism Seek and Find 3: Comparison (SF4)
10 Reading 3-2	Nov 2 Lecture:	Nov 4 Lecture:	Nov 6 Content Survey 3: Principles and Formalism Design Warmup 3: Working with Census Data
11	Nov 9 Lecture:	Nov 11 Lecture:	Nov 13 Anonymous Survey 3: Check In Design Exercise 3: Census (aggregations)
Module 4: Standard (Hard) Problems
12 Reading 4-1	Nov 16 Lecture:	Nov 18 Lecture:	Nov 20 Reading Survey 4: Hard Problems Seek and Find 4: Graphs
13 Reading 4-2	Nov 23 Lecture:	Nov 25 Lecture:	Nov 27 Thanksgiving Break Design Warmup 4: Experiment with Flight Data (distributions)
14	Nov 30 Lecture:	Dec 2 Lecture:	Dec 4 Content Survey 4: Hard Problems Design Exercise 4: More Flight Data
Wrap Up
15 Reading 5-1	Dec 7 Lecture:	Dec 9 Lecture:	Dec 11 Anonymous Survey 4: Class Survey Design Exercise 5: Portfolio (Resubmissions)

GAI Policies

Mon, 24 Aug 2026 17:49:44 -0500

Summary: Use AI tools (Claude, ChatGPT, Co-Pilot, etc.) to help you in your learning, not to do the assignments for you. Treat them like another student: you can get them to help you, but you are responsible for your own work. Give them proper credit / attribution. Don’t claim their work as your own.

Course Learning Outcomes

Mon, 24 Aug 2026 17:49:17 -0500

Course learning outcomes explain what we are trying to achieve in the course. For the student, it gives you a sense of what I (as instructor) am trying to do. As instructor, it guides the design of the class.

What and Why

Mon, 24 Aug 2026 17:48:18 -0500

This class is a principles-and-design-oriented exploration of Data Visualization. This posting will explain the content, style, and rationale for the class. The class is different from most other CS classes.

Getting Started

Mon, 24 Aug 2026 17:47:46 -0500

Here’s what you should do to get started…

Understand what this class is about - please read the What and Why page (and maybe the Course Learning Outcomes) which will give you a sense of what this class is about. Reading the first tutorials can give you the philosophy of the course in a nutshell. This isn’t your standard CS class. If this class isn’t for you, we won’t be offended if you drop early.
Understand how the class will work - look at Policy Overview page to get an idea of the mechanics. The Syllabus has details about policies, but also a bit of the description of the content.
Be prepared for class - class attendance is required. Please bring drawing supplies (pens or pencils, in multiple colors - I recommend black + four other colors)

Attendance is part of class. This class involves in-class experiences. This requires students to be in class - if you are not in class for the in-class experience, you won’t have the in-class experience. If you know that you will miss a lot of classes, or do not intend to come to class “nearly all of the time”, please do not take the class.

Policy Overview

Mon, 24 Aug 2026 17:45:53 -0500

Summarizing the policy related contents of the Syllabus…

Syllabus

Mon, 24 Aug 2026 17:45:08 -0500

This is a Syllabus in the form of the official University Template. It details the course policies. A summary of course policies is available at Policy Overview

More information is on the course web page: https://pages.graphics.cs.wisc.edu/765-26/.

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Mon, 13 Jul 2026 00:00:00 +0000

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