Course Web for CS 765 Data Visualization

Week in Vis 3 Mon, Sep 16-Fri, Sep 20

• Mon, Sep 16 – Abstractions
• Wed, Sep 18 – ICE: standard designs
• Fri, Sep 20 – OPT: Tableau Tutorial
• Reading: Week 3 – Abstraction (due Mon, Sep 16 – preferably before class)
• Online Discussion 03: Abstraction (first post due Tue, Sep 17)
• Design Challenge: DC1: Data Set Selection (due Wed, Sep 18)
• Quiz 03: Abstraction (due Fri, Sep 20) – note that the quiz may not be available before Tuesday
• Seek and Find 03: Abstraction (due Fri, Sep 20)

We’ve finished our second week – which means we’ve been through a “regular” week. Hopefully, you are getting with the weekly rhythm.  Readings for class Monday, online discussion post before Tuesday, quiz and seek and find due on Friday. Now we also have Design Challenges (with the first phase of the first challenge due on Wednesday).

Content-wise, this week, we’ll talk about abstraction, as a mechanism to understand how to apply visualization to data. We’ll talk briefly about tasks, and focus on data abstraction. We’ll also talk about how data type influences design (mainly in the ICE on Tuesday) especially for the standard data types. This is good preparation for Design Challenge 1 (which is starting this week).

If you haven’t already looked over Design Challenge 1, you should do so. While Wednesday’s deadline is soft (see the description), you probably should get started. Friday in class we will have an (optional) tableau tutorial.

In terms of online discussions, your focus should be Online Discussion 3 and Seek and Find 3, although we leave last week’s discussions open so you can continue to discuss.

Readings for the Week

The topic for this week’s readings is Abstraction – especially data abstraction.

1. Shneiderman, B. (1996). The eyes have it: a task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE Symposium on Visual Languages (pp. 336–343). (doi) (web pdf)

   This is a classic. Possibly one of the most influencial papers in the field. It’s old, and newer things are far more extensive. And the field has moved on from 1996 in many ways. But the initial thinking of abstracting data and task separately, and suggesting what those abstractions might be, really started here. The information seeking mantra is a classic notion. This paper is dated enough that it can be hard to read – but it is short.

2. What: Data Abstraction (Chapter 2 from Munzner’s Visualization Analysis and Design) (Munzner-02-DataAbstraction.pdf 1.1mb)

   A fairly dry description of the types of data. Don’t worry about trying to remember all the terms – you can always look them up when you encounter them again.

   Despite it’s length, the chapter skips a key concept: level of measurement for scales. You might have learned this in a stats class, but please understand the difference between “scale types” (nominal, ordinal, interval, ratio). Usable Stats has a simple introduction.

3. Why: Task Abstraction (Chapter 3 from Munzner’s Visualization Analysis and Design) (Munzner-03-TaskAbstraction.pdf 0.4mb)

   Figuring out how to think about tasks is important. This chapter (and the research paper it is derived from) focuses too much on trying to put every task in a neat organization. What’s important is to think about tasks. This is one way to do it, and it will help you learn to think about tasks. Don’t get too bogged down in all of her categories.

   We’re reading the book chapter, not the paper. I recommend the Schulz et. al paper below for contrast.

4. Forms and Functions (Chapter 2 of The Functional Art) (theFunctionalArtCh2.pdf 8.2mb)

   Cairo’s thinking about “the shape of data” is another way to think about data abstraction in a less academic way.

Optional

1. Mackinlay, J., Hanrahan, P., & Stolte, C. (2007). Show me: automatic presentation for visual analysis. IEEE Transactions on Visualization and Computer Graphics, 13(6), 1137–44. (DOI) (Mackinlay2007-ShowMe.pdf 0.6mb)

   This is a research paper, but it’s an unusual one. It’s easy to dismiss this paper as marketing for Tableau – but it really does give a sense of how good abstractions can help in choosing appropriate visualizations. It is timely, since Tableau will come up in class.

2. Schulz, H.-J., Nocke, T., Heitzler, M., & Schumann, H. (2013). A Design Space of Visualization Tasks. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2366–2375. (doi) (web pdf)

   This paper takes a quite different approach to Munzner in thinking about tasks. It came out at the same time as the paper behind the book chapter. It was literally in the same session of the conference. I actually find this to be a more useful way to think about task – it’s not as encyclopedic, but that’s a feature.

3. Sarikaya, A. and Gleicher, M. Scatterplots: Tasks, Data, and Designs. IEEE Transactions on Visualization and Computer Graphics, 24(1) — Jan 2018 . (web page)

   An recent paper that Alper (a former student) and I wrote. It focuses on a specific (but ubiquitous) kind of visualization, but thinks through the tasks and shows how thinking about the data properties and tasks helps suggest designs. I like this paper, but I am biased.

Week in Vis 2 Mon, Sep 9-Fri, Sep 13

• Mon, Sep 9 – Why Vis
• Wed, Sep 11 – ICE:critiques(2)
• Fri, Sep 13 – No Class
• Reading: Week 2 – Why Visualize (due Mon, Sep 9 – preferably before class)
• Online Discussion 02: Why Visualize (first post due Wed, Sep 11)
• Quiz 02: Why Visualize (due Fri, Sep 13)
• Seek and Find 02: Why Visualize (due Fri, Sep 13)

Week number 2 – we’re still getting things set up and not in the weekly rhythm, but hopefully, but the end of this week we’ll be in steady state.

First: if you haven’t done week 1’s work, please do it! We’ve extended the deadlines so that you can. The first readings are helpful preparation for this week. And we do want you to do all of the online discussions and seek and finds.

Note: the online discussions (both the “Online Discussions” and the Seek and Finds) stay “open” for discussion 1 week after the due date so that people can continue to discuss the initial postings.

The Quiz will not be available until after class Monday – or maybe Tuesday. It’s not due until Friday.

This week there are two (somewhat independent) topics. The lecture (and main readings) ask the question “why visualize?” This is another big reading week. Understanding why we might want to do visualization will be important to understand what it means to do it well.

The other topic is more skills-based: we’ll learn about how to do critique. There is a reading to get you thinking about it. Critique is a useful skill – not just for visualization and design. It’s something we need to do all the time, but rarely think about as a skill. Hopefully, the reading and in-class practice will help you develop your skill at critique.

Readings for the Week

The main readings are intended to give you a sense of why we do visualization, and why we bother to try to do it correctly. If you haven’t done the first week’s readings, please do them first.

Again, there is a lot of reading this week, because there is no design challenge yet.

1. The Beauty Paradox (Chapter 3 of Cairo’s The Functional Art) (theFunctionalArtCh3.pdf 11.4mb)

   This chapter gets into the philosophy of evaluation. Cairo has an interesting (and non-academic) perspective. We’re reading this now (rather than when we get to evaluation) because it’s good food for thought, and it has a good discussion of Tufte, so you’re prepared when you read him next.

2. Graphical Excellence (Chapter 1 of Tufte’s The Visual Display of Quantitative Information) (1-VDQI-1-GraphicalExcellence.pdf 33.8mb)

   Tufte’s fame, style and personality can get in the way of his message. Cairo (above on the list) will help us understand that. But, there’s no denying that Tufte has had influence – and there is a lot to learn from him.

3. The Dance of Meaning (Chapter 9 of Visual Thinking for Design) (Ware-9-Meaning.pdf 2.7mb)

   Yes, we’re reading the last chapter first. You might want to skim through the book leading up to it (I basically read quickly) it in one sitting. Reading the ending might motivate you to read the whole thing (which we will later). The perspective here is how the perceptual science might suggest why vis is interesting.

4. The first 17 pages of the Introduction to “Information Visualization: Using Visualization to Think” by Card, Mackinlay, and Schneiderman (01-InfoVis-CardMackinlaySchneid-Chap1.pdf 77.4mb) .

   This is a 1999 book that consists of this intro, and a bunch of seminal papers. The examples are old, but the main points are timeless. It is the best thing I know of that gets at Vis from the cognitive science perspective. The rest of the chapter (past page 17) is good too, but more redundant with other things we’ll read – so it’s optional. Although, every time I go back to it, I am amazed how good this is – despite being old.

Unrelated to the main topic, we will be talking about how to critique and practicing critique in class. Usually, we just critique – but one of my goals in this class is to teach people to do it more effectively. This chapter (which is part of a whole book on how to critique productively) will hopefully give you some things to think about, although ultimately, I think it just takes practice.

• “Understanding Critique,” Chapter 1 of Discussing Design by Adam Conor and Aaron Irizarry, O’Reilly Books, 2015. Chapter available online as a sampler from the publisher. (pp. 7-25, 18 pages)

Optional Readings

There’s already a lot to read, so I cannot require you to read these. But they are really valuable. The Tufte chapter is a classic. Both were required in earlier versions of the class.

0. Visual Statistical Thinking (3-VE-2-Visual-Statistical-Thinking.pdf 25.1mb)

   Chapter 2 “Visual Statistical Thinking” from Tufte’s Visual Explanations (pages 26-53; 27 pages) . This is Tufte at his best/worst: describing two historical examples (John Snow’s map of the London Cholera Epidemic and The Challenger Disaster). His oversimplification of the role of visualization in these situations makes his points forceful, but not as black-and-white as he tries to make them. This used to be required, and may be discussed in class.

1. Why Visualize: From Information to Wisdom Preface and Chapter 1 of The Functional Art (online at publisher) (theFunctionalArtCh1.pdf 7.8mb)

   This is a great introduction to thinking about data presentation from a journalists perspective, with Cairo’s great use of examples, clarity, and connection to a bigger picture. It’s optional since it’s a little off topic (it’s more about Data Journalism), and a little redundant with the other Cairo readings.