Readings

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.

How are the readings organized?

To make the readings more manageable, I am dividing them into different categories. The motivation is described below. Generally, backbone and core will be assigned in the first week of the module, and advanced and experiential will be assigned in the second.

• backbone - Read this carefully. These are the key pieces of the class - often the things I will write to tell you how they fit into the class. I want you to learn the content the way I want you to learn. Expect questions on the reading survey.
• core - Learn this. These are readings that contain important content that I want you to learn. The important thing is that you learn it; learning it from secondary sources (like AI summaries) is OK as long as you get it. My goal is to provide good summaries of these papers that give you sufficient content for class, and hopefully inspiration to read more. Refer to the originals if you want more depth. Expect questions on the reading survey.
• advanced - Look at this. This is content I want you to know. But realistically, students are only going to invest so much energy in the class. I recommend that you skim the papers or read summaries and dig deeper if you want more. May be useful for the content surveys.
• experiential - Experience this. This is a case where I want you to actually read the original source for the experience of reading the original source. It’s not just about the content: I want you to read the original source. As a “graduate student level” practitioner or researcher, you need practice at reading primary sources. Every module we will have two: of different types. Expect questions on the content surveys.
  • historic - old documents. Reading old documents is useful to see where foundational ideas come from, and to extract lessons that are still relevant. However, these papers can be tricky to read because they have different contexts and different styles.
  • modern - recent papers. Recent papers show not only the newest advances in the field, but also give the reader exposure to how the field “works”.
• optional - Explore this if you’re interested. These are suggestions if you want to go further into a topic, or see some papers that I liked that I simply cannot fit into class.
• resource - Refer to this if you need it. These are recommended things to look at as reference material, such as practical advice for design.

Why a new strategy towards reading?

The Readings, all on one page!

For various reasons, it is useful to have the readings for the semester all on one page - they also appear on the module pages.

Module 0: Welcome: What is Vis?: Week 1

The first required reading is the course web. Make sure that you’ve looked at the Syllabus and Parts of Class and Rubrics to understand how things work. Read What and Why to understand the philosophy of the class. The top of the Readings page will explain how readings work.

The backbone of this week’s reading consists of some tutorials that will give you a lot of my philosophy. You are also required to read two chapters from Alberto Cairo’s The Functional Art and one from Munzner’s Visualization Analysis and Design. Sorry, I don’t have summaries of these yet, you actually have to read them.

• backbone Michael Gleicher. Tutorial 1: What is Vis. Vis Snacks Tutorial 1. (url)
• backbone Michael Gleicher. Tutorial 2: A Simple Example 4 Design Moves on a Table (OBSOLETE). Vis Snacks Tutorial 2. (url) - Note: this really is the “old/obsolete one”. Reading the new tutorial 2 is optional for now. We’ll read it next module.
• backbone Michael Gleicher. Tutorial 3: What is Easy to See?. Vis Snacks Tutorial 3. (url)
• backbone Alberto Cairo. Forms and Functions. Chapter 2 of The Functional Art. (Canvas File) (UW Library) - Note that you are starting with Chapter 2. I recommend starting with the beginning, but that is optional.
• backbone Alberto Cairo. The Beauty Paradox. Chapter 3 of The Functional Art. (Canvas File) (UW Library)
• backbone Tamara Munzner. What's Vis. Chapter 1 from Munzner's Visualization Analysis & Design. (Canvas File) (video) (UW Library) - Munzner’s VAD is the “core textbook” for the class. See Munzner's Book. The introductory chapter gives her philosophy.

See Cairo's Books for a discussion of Cairo’s books. I like them a lot. I really recommend starting reading at the beginning (rather than the required Chapter 2). These are light reading, and highly recommended. I felt like all of the chapters were a bit much to require.

• optional Alberto Cairo. The partnership of presentation and exploration. Preface of The Functional Art. (Canvas File)
• optional Alberto Cairo. Why Visualize: From Information to Wisdom. Chapter 1 of The Functional Art. (Canvas File) (web pdf) (UW Library)

Module 0: Welcome: What is Vis?: Week 2

This week we only have experiential readings: I want you to read these two documents for the experience of reading them. The content survey will ask you about them.

They are weird readings… and this is an experiment. Both readings are long. But they have lots of pictures, and there isn’t much else to do for class.

For the historic reading, we’ll read the first Chapter of Tufte’s first book. This is an important historical document, generally credited as starting the field. Tufte is interesting as a historical character (last week, you read Cairo's discussion of him (FA3)).

For the modern modern reading, we’ll read a recent survey “paper” covering the field. I put paper in quotes because it’s long enough to be considered a book unto itself (80 pages in double spaced format, 50+ in journal form). It’s good practice for reading at a high level: you can’t catch all the details. Get a sense of how science (or, at least, a particular kind of it), can inform visualization.

• historic Eduard Tufte. Graphical Excellence. Chapter 1 of Tufte's The Visual Display of Quantitative Information. (Canvas File)
• modern Steven Franconeri, Lace Padilla, Priti Shah , Jeffrey Zacks, Jessica Hullman. The Science of Visual Data Communication: What Works. Psychological Science in the Public Interest, 22 (3)(December 2021). (Canvas File) (doi) (web pdf) (url)

There is an intentional contrast: the Franconeri et al. survey paper specifically focuses on the psychological science - what about visualization can we know from the scientific literature; Tufte generally asserts his opinions as fact without any regard to the actual science (to be far, this writing pre-dates the scientific study of Visualization).

I find it very easy to be negative about Tufte. But (1) there is no denying that he has had a huge impact on the world of Visualization outside of academia; and (2) there are positives to get out of it.

As you read:

• Keep this in context: it was 1983. The Visualization as a subject onto itself did not exist yet.
• Try to notice the negatives (e.g., when he expresses preferences as principles, or doesn’t support his claims).
• Note the positives (e.g., the use of real examples)
• Think of his assertions as “points to consider.” Think about how they might be explored more rigorously.

Module 1: Building Blocks: Week 1

This week, you need to get up to speed on a bunch of the different building blocks we will need for class. There are alot of different pieces to get all at once. And each piece has some amount of reading to go with it.

The main thing is to read a little bit about each of the topics. I tried to make sufficient summaries for each topic. And then you can read more if you’re interested.

My intent was to write tutorials about each of the topics to give you a quick summary. And then you could read more as you had time. However, I didn’t get to actually write the tutorial on encodings - I’ll give you a “Claude-authored” tutorial, but probably you should read the Munzner chapters.

• backbone Michael Gleicher. Tutorial 2: How to Think about Visualization: Building Blocks. Vis Snacks Tutorial 2. (url)
• backbone Michael Gleicher. Tutorial 4: Critique. Vis Snacks Tutorial 4. (url) - read my tutorial to be ready for class. Reading more is optional.
• backbone Michael Gleicher. Data Abstraction Cheat Sheet. Vis Snacks Tutorial. (url) - my summary of the key things. Read it first. Read What: Data Abstraction if there is anything you need more clarity on.
• backbone Michael Gleicher. Task Abstraction: A Crash Course. Vis Snacks Tutorial. (url) - my summary of the key things. Read it, and read more if you are interested - it’s full of pointers.
• backbone Claude (Mike can't take credit). Encodings: Building Blocks for Visualizations. Vis Snacks Tutorial. (url) - this is Claude’s summary of encodings. It’s decent, but I think you should read the two munzner chapters to get the key ideas.
  • core Tamara Munzner. Marks and Channels. Chapter 5 from Munzner's Visualization Analysis & Design. (Canvas File) (video) (UW Library) - Munzner covers most of encodings in this chapter.
  • core Tamara Munzner. Arrange Tables. Chapter 7 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library) - Munzner divides layout (position encodings) from all other encodings, so this is a separate chapter

Module 1: Building Blocks: Week 2

For this week, we have 3 experiential readings (sorry, I had to add an extra - but it’s quite light).

One reading is an essay to add to our readings on critique. It’s sortof halfway between historical and modern. It isn’t a paper: it’s an essay. Some context: when they wrote this, the authors were already becoming famous for being the bridge between the academic research community and the practitioner community.

• historic Fernanda Viegas and Martin Wattenberg. Design and Redesign. Medium Posting. (Canvas File) (url) (Summary) - This essay is really valuable. And it is a case where the document itself is historically interesting, and their examples are worth looking at. This is valuable for seeing how far we’ve come at bringing design to visualization.

The “regular” experiential readings are two papers about Graphical Perception - the “science” of trying to understand encodings empirically.

The key context: the whole field of graphical perception started with a paper by Cleveland and McGill in 1984. There were early perceptual science papers, but this is the first time “visualization researchers” (in scare quotes since in 1984 they wouldn’t have identified themselves this way) tried to do experiments to inform chart design choices.

I am not requiring you to read the original 1984 paper (it is optional). Instead, I want you to read a 2010 paper that reproduces and extends the results, and a more current paper that challenges the paradigm.

• historic Jeffrey Heer, Michael Bostock. Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design. (doi) (web pdf) (url)
• modern Caitlyn M. McColeman, Fumeng Yang, Steven Franconeri, Timothy F. Brady. Rethinking the Ranks of Visual Channels. IEEE Transactions on Visualization and Computer Graphics (Volume: 28, Issue: 1, January 2022). (doi) (web pdf) (url)

The first paper was one of the earliest examples of using crowd-sources participants for visualization studies - something which is now totally standard practice. Many of us were starting to try it at the time (Detection of Image Stretching was our paper that came out around the same time). But Heer and Bostock really got it in widespread attention.

The second paper is notable not only because of its conclusion and interesting method but also for its statistical modeling and the visualizations they use to convey their results. It’s a great example of visualization applied to visualization research.

Module 2: Methodology: Making and Using Visualizations: Week 1

There are 3 parts to this week’s reading: general implementation, learning about toolkit you might use, and learning about design strategies. There is an experiential reading (one that I want you to read carefully).

Thing 1: General Implementation: watch this video of Prof. Dominik Moritz’s guest lecture in class in Fall 2020:

• Dominick Moritz. Dominick Moritz's Guest Lecture. (video from CS765 2020 - in Kaltura Mediaspace). (video)

Thing 2: Read about libraries you might use: I want you to read about 2 different visualization “toolkits” that might be relevant for you. I use the term “toolkit” to refer generically to libraries, packages, APIs, etc.

You should pick 2 things that you are likely to use. If you like to program in Python, pick 2 Python libraries.

I’d like you to pick a “high-level” (in terms of level of abstraction) toolkit and a “low-level” one. The concept of level of abstraction should be clearer after the lecture. Of course, you might not know the level of abstraction until after you read about the toolkit. That’s OK - think about how the two relate to each other (“high/low level” can be relative). (hint: that’s a reasing survey question).

Thing 3: Read about design strategies: Comparison and Summarization: These will be useful in designing visualizations, and are referred to in the assignments.

The key reading (that I really want you to read - it’s an “experiential paper”) is my Considerations of Comparison paper. The summary will get you the key points, but I want you to actually read the paper because I think the examples are good, and the depth and connection to other aspects of class is useful. And I am really proud of it. You can read the summary as well - but the paper is required.

• modern Michael Gleicher. Considerations for Visualizing Comparisons. IEEE Transactions on Visualization and Computer Graphics (Proc. InfoVis '17), 2018. (doi) (url) (Summary)

There is a related paper on summarization. For this one, it’s OK to read the summary, but you might want to skim over the paper as well:

• backbone Sarikaya, Gleicher and Szafir. Design Factors for Summary Visualization in Visual Analytics. Computer Graphics Forum 37(3) (Proceedings EuroVis 2018). (doi) (url) (Summary)

There are two book chapters that connect with this. There’s already a lot of reading this week, but do have a look, especially at Chapter 13. It’s a broader view of the summaries paper. These chapters are fairly short, skimmable, and they have a lot of pictures.

• backbone Tamara Munzner. Reduce Items and Dimensions. Chapter 13 from Munzner's Visualization Analysis & Design. (Canvas File) (video) (UW Library) - Scalability strategies
• backbone Tamara Munzner. Embed: Focus+Context. Chapter 14 from Munzner's Visualization Analysis & Design. (Canvas File) (video) (UW Library) - Focus+Context is a scalability strategy

Module 2: Methodology: Making and Using Visualizations: Week 2

This weeks reading continue our examination of implementation, design stategies, and exploration.

You need to:

1. Do something to learn about a “grammar of graphics” based tool or toolkit. Reading a paper about a grammar-based tool is optional.
2. Read a paper about an experimental toolkit.
3. Read a very short paper that helps describe how to think about statistics and exploration.

There will be questions about all three in Content Survey 2: Implementation and Methodology (due Fri, Oct 16).

Part 1: Learn about a Grammar-of-Graphiucs-Based Tool: You can learn about either Vega-Lite (or Altair, its Python bindings), or Tableau.

To learn about VegaLite (or Altair, it’s Python binding) go through the the first 2 “Chapters” of the UW Visualization Curriculum. (UW is the other UW, not us). I recommend that you watch the video first (its also linked in chapter 1). (Chapter 3 is optional, but recommended if you want to really understand or use the tool). Reading the technical paper for Vega-Lite gets at the ideas more directly.

Alternatively, learn about tableau (see Tableau Access for CS765). Here, you’re kindof on your own: but play with it enough (and read/watch enough tutorials) that you can make something by using the grammatical elements (identifying variables, tying them to encodings, using layouts, …).

Either way, the content survey asks you to describe what you did.

Part 2: Read a Research Paper: Read this paper. This isn’t a practical toolkit to use, but it is good food for thought, and an example of a modern technical paper to practice reading. It’s a best paper award winner. This can be a hard paper to read because it has a bunch of technical bits unrelated to visualization.

• modern Dominik Moritz, Chenglong Wang, Gregory Nelson, Halden Lin, Adam M. Smith, Bill Howe, Jeffrey Heer. Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco. IEEE Transactions on Visualization and Computer Graphics, (Proc InfoVis 2019), 25(1). (doi) (url)

A core question to think about as you read: what is different about this (Draco) than all the other toolkits you’ve read about?

Part 3: Read a Short Article on Statistics: This paper is less than 2 pages. And it’s about statistics (or data analysis), not visualization. But it calls to question a key point: what can we say about an analysis (or something we see in a visualization).

• core J. T. Leek and R. D. Peng. What is the question?. Science 347, 6228 (March 2015), 1314–1315. (doi) (web pdf)

My favorite way to think about this is in terms of the “three statistical tasks”: description, explanation, and prediction. I’ll explain that in class because there are no appropriate readings.

Module 3: Principles and Formalism: Week 1

1. backbone Tamara Munzner. Analysis. Chapter 4 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library) (Summary) - OK to read summary
2. backbone Alberto Cairo. The five qualities of great visualizations. Chapter 2 of The Truthful Art. (Canvas File) (UW Library) - Cairo’s 5 qualities of great visualizations: a way to think about evaluation to contrast the more academic works.
3. historic Card, Mackinlay, and Schneiderman. Information Visualization. The first 17 pages of the Introduction to “Information Visualization: Using Visualization to Think. (Canvas File) - Only the first 16 pages (there are lots of pictures)
4. core Steve Franconeri. Thinking with Data Visualizations, Fast and Slow. Open Vis 2018 Conference Talk. (video) (Summary)
5. modern Danielle Albers; Michael Correll; Michael Gleicher. Task-Driven Evaluation of Aggregation in Time Series Visualization. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '14), 551–560, May 2014. (doi) (web pdf) (url)
6. optional Chris North. Visualization Viewpoints: Toward Measuring Visualization Insight. IEEE Computer Graphics & Applications, 26(3): 6-9, May/June 2006. (doi)
7. optional Gordon Kindlmann and Carlos Scheidegger. An Algebraic Process for Visualization Design. IEEE Transactions on Visualization and Computer Graphics, 20(12) 2014.. (doi) (web pdf) (Summary)
8. optional Danielle Albers Szafir; Steve Haroz; Michael Gleicher; Steven Franconeri. Four Types of Ensemble Encoding in Data Visualizations. Journal of Vision, 16(5):11, March 2016. (doi) (web pdf) (url)

This week there are 4 required readings and 1 required “watching”. This is a first week of module reading load - and it isn’t so bad because at least one the summary is OK. (working on summaries for others)

Evaluation: Reading #1 (the Munzner Nested Model book chapter) is so important and central to the class that I recommend you read my summary of it first. The summary will help you appreciate why it is so important. Read #2 Cairo to get his “non-academic view”. #6 (North’s Measuring Insight) gets at why its so hard to assess visualizations - but we’ll get the main points in lecture.

#7 is optional - I’ll mention it in class, but its a nice example of how an elegant formalism can be useful in thinking about visualizations. Reading the summary is a start.

Cognition and Perception: Reading #3 (Card et al) and Watching #4 (Franconeri video) will introduce you to the cognitive and perceptual aspects. Watch the video for #4 (the summary gets some key points, but not as well).

Reading #3 is an experiential reading: this is a foundational document in the field. They were naming and defining the field of Information Visualization, and describing the cognitive science basis it builds on. The section “How Visualization Amplifies Cognition” (starting on page 15), with Table 1.3 is particularly important. It really gets at why visualizations help us do things. (you can stop after the table on page 16) Even though this is from 1999 (and is dated in many ways) its both a great history of the field and still stands up as an introduction to the cognitive aspects of visualization.

Empirical Evaluation: Reading #5 is meant to give you a taste of empirical papers, and to introduce you to a different perceptual phenomenon that is useful in visualization: ensemble coding. The paper is a set of clean, simple experiments. It also gets at a really interesting aspect of perception: the ability of the eye to make judgements over groups of marks. If you want to learn more about ensemble coding, optional reading #8 give a survey (of everything up to 2016 - there’s a ton of new stuff).

Module 3: Principles and Formalism: Week 2

1. core Karen B. Schloss. Perceptual and Cognitive Foundations of Information Visualization. Annual Review of Vision Science 11:303–330 (2025). (doi)
2. backbone Colin Ware. The Dance of Meaning. Chapter 10 of Visual Thinking for Design, or Chapter 10 of the newer Visual Thinking for Information Design. (Canvas File)
3. backbone Tamara Munzner. Map Color and Other Channels. Chapter 10 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library)
4. modern Cindy Xiong; Lisanne Van Weelden; Steven Franconeri. The Curse of Knowledge in Visual Data Communication. IEEE Transactions on Visualization and Computer Graphics (Volume: 26, Issue: 10, October 2020). (doi) (web pdf)
5. optional Alberto Cairo. The Eye and Visual Brain. Chapter 5 of The Functional Art. (Canvas File) (UW Library)
6. optional Alberto Cairo. Visualizing for the Mind. Chapter 6 of The Functional Art. (Canvas File) (UW Library)
7. optional Brian Ondov; Nicole Jardine; Niklas Elmqvist; Steven Franconeri. Face to Face: Evaluating Visual Comparison. IEEE Transactions on Visualization and Computer Graphics (Volume: 25, Issue: 1, January 2019). (doi)
8. optional Brian D. Ondov; Fumeng Yang; Matthew Kay; Niklas Elmqvist; Steven Franconeri. Revealing Perceptual Proxies with Adversarial Examples. IEEE Transactions on Visualization and Computer Graphics (Volume: 27, Issue: 2, February 2021). (doi) (web pdf)
9. optional Borland, D., & Taylor, R.. Rainbow Color Map (Still) Considered Harmful. IEEE Computer Graphics and Applications, 27(2), 14–17. (doi)
10. optional Colin Ware, Maureen Stone, Danielle Albers Szafir. Rainbow Colormaps Are Not All Bad. IEEE Computer Graphics and Applications, Volume 43, Issue 3, 2023. (doi) (web pdf)
11. optional Kennedy Elliot. 39 Studies about human perception in 30 minutes. Medium Posting. (url)
12. resource Ghulam Quadri and Paul Rosen. A Survey of Perception-Based Visualization Studies by Task. IEEE Transactions on Visualization and Computer Graphics 28, 12 (December 2022). (doi) (web pdf) (url) - resource readings are optional
13. resource Evanthia Dimara, Steven Franconeri, Catherine Plaisant, Anastasia Bezerianos, Pierre Dragicevic. A Task-based Taxonomy of Cognitive Biases for Information Visualization. IEEE Transactions on Visualization and Computer Graphics (Volume: 26, Issue: 2, February 2020). (doi) (web pdf) - resource readings are optional

Yes, this is a long list - but most of them are optional. And I could give a huge list of readings on color alone…

Perception: Read #1 (Schloss) to get a thorough overview of the perceptual aspects of visualization (Karen is a Prof. in our Psych Department). Read #2 Ware to get a less formal description, that is more tied to how perception is tied to design practice. Reading #5 and #6 (Cairo) is interesting for his non-scientific (designer’s intuition) take on perception and cognition.

Empirical Studies: #4 (Xiong et al.) is a good example of a modern emprical study paper. Read it to get a sense of how experiments are used to support arguments. It will also give you an introduction to cognitive biases. Reading #11 (optional) will give you a quick, informal tour through a number of key emprical results. Reading #13 (Quadri&Rosen, optional) will give you a survey of many of the studies about perception in visualization - it’s a well organized library, keep it in mind when you want to know what is out there. #7 and #8 are two other optional examples of empirical papers.

Color: I don’t even know where to begin. I love the topic, and it is suprisingly complicated, and there are many different angles. Read #3 (Munzner VAD Ch 10) to get a quick introduction. #9 and #10 talk about rainbow color maps - which is a good example of how many of the color perception issues connect.

Module 4: Standard (Hard) Problems: Week 1

• backbone Tamara Munzner. Arrange Spatial Data. Chapter 8 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library) - Spatial data is the important case for most “traditional” scientific and medical data (as well as cartography). This will give you a brief taste.
• backbone Tamara Munzner. Arrange Networks and Trees. Chapter 9 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library) - Network (graph) data is common and there are a variety of approaches. This will give you a quick survey.

Module 4: Standard (Hard) Problems: Week 2

Wrap Up Module