CS 765 will be offered again in the Fall of 2019.

See the CS765-2019 Web Page.

Some questions that people ask:

Syllabus: the class will be very similar to the 2018 offering, so look at the 2018 web site. The Course Announcement is a good place to start. Some details will change, and we will probably encourage people to experiment a bit more with web-based visualization tools.

Enrollment: all enrollment is done via the waiting list (except for a few early birds). We cannot begin to manage the waiting list until we see the demand and make sure there is space for incoming students. Last year, all students who were on the waiting list were ultimately given the opportunity to enroll.

Undergraduates: we will allow some undergraduates to enroll in the class. You need to go through the waiting list process. You also need to fill out a permission request with CS Department Enrollment Management <enrollment@cs.wisc.edu>.

Is this class appropriate for me? This class is meant for anyone who works with data, and therefore, has a need to understand how we try to understand it. In the past, it has been “programming optional” – however, in the future, we may have some assignments that require you to do some programming.

This is the website for the 2018 edition of CS765. You may be looking for the 2019 Web Page?

Weather

• U.S. climate
• U.S. weather
• Weather data
• Australian Baseline Sea Level Monitoring Project
• National Oceanic and Atmospheric Administration: Sea level trends
• U.S. Environmental Protection Agency

Statistics by Country

• Life expectancy
• GDP

Travel

• Airline statistics
• Various traffic datasets
• Chicago average daily traffic counts

Stocks

• U.S. stock market
• New York Stock Exchange: S&P 500

Other

• U.S. baby names
• San Francisco Library Usage
• CPU usage
• Various datasets: business, health, population, tourism…

Final grades have been posted to the registrar’s system.

Grades for DC3 were posted to Canvas along with brief comments – we didn’t have time to write extensive feedback.

Computing final grades worked out almost exactly as described when the semester began:

We averaged 6 things:

• 3 design challenges
• A Discussion Grade, A Seek and Find Grade (as mentioned at the beginning of the semester, the quantitative measures for these max out at an AB).
• For “participation” we gave everyone an AB, unless there was a problem. We took our subjective opinion into account for border cases.

For border cases, we moved people up.

Generally, to get an A, you needed a better than AB average on the Design Challenges.

We were less likely to move someone up if they missed a lot of in class exercises (without telling us), or were often late with assignments, … In these cases, people got their numerical averages.

If you’re curious, more people got As than any other grade (almost half the class).

Sorry for the late notice, but class is cancelled on Wednesday 12/12.

Class Meetings

• Mon, Dec 10 – Lecture:SciVis
• Wed, Dec 12 – Lecture:Summary
• Fri, Dec 14 – No Class: Semester Over

Week Deadlines

• Reading: Week 15 – SciVis and Research (due Mon, Dec 10 – preferably before class)
• Quiz 15: 15: (due Tue, Dec 11)
• Online Discussion 15: Vis Research (first post due Wed, Dec 12)
• Seek and Find 15: Pick Something (due Fri, Dec 14)
• Design Challenge: DC3:Final (due Fri, Dec 14)

If you haven’t done a course evaluation, please do it! https://aefis.wisc.edu/

Last week we wrapped up talking about graphs, did the route maps exercise, watched cartoons, and I ranted about presentations.

There is class this week – it may seem anti-climatic, but there is still more to talk about. We won’t get to do everything.

Monday’s lecture will be able “Traditional Scientific Visualization” – basically, a survey of things that would be in a traditional visualization course. It’s a different kind of visualization topics.

Wednesday’s lecture will be a summary day. A chance to look back over the semester and reflect on what we’ve been through. We’ll use this as a chance to talk about visualization research directions – with a focus on what I am interested in. Sadly, we didn’t get much time during the semester to talk about visualization for machine learning, helping with decision making under uncertainty, designing summaries of collections of complex objects, … – so maybe we can talk about that.

You may be wondering “what is visualization research” – and this week’s assignment (and Wednesday’s class) should give you an idea. We’ve focused the semester on things that visualization knowledge knows how to do – now we’ll look beyond to the kinds of things we still need to figure out.

You may want to look at this week’s learning goals Learning Goals 15: Week 15 – Visualization Research.

Oh – and there’s that Design Challenge due on Friday.

Readings (due Mon, Dec 10 – preferably before class)

Two seemingly separate things. But, a large chunk of visualization research is on the topic of “Scientific Visualization” – which we didn’t touch this semester.

For Scientific Visualization, there is nothing I know of that is at the right level of detail. The chapter from Munzner will give you some of the basic concepts.

• Arrange Spatial Data (Chapter 8 from Munzner’s Visualization Analysis & Design) (Munzner-08-ArrangeSpatial.pdf 1.0mb)

I want you to have a sense of what visualization research is nowadays. What I’d like you to do is…

Look at the titles of the papers from either the 2018 or 2017 Vis conference. Notice that there are 3 separate sub-conferences (VAST, InfoVis, and SciVis). From looking at the titles, you can hopefully get a sense of what the topics are. There are 25 second video previews, and links so you can get the actual papers (via the IEEE digital library). You can look at the 2016 lists if that’s more convenient. (warning the 25 second previews aren’t always that useful – making informative 25 second videos is hard, and the quality is variable)

• 2018 Session List is organized in the order of presentation, but it has links to the “video previews” (25 seconds) that have the abstracts on the pages. Unlike the 2017 page, there are no links to the papers themselves. The 2018 Accepted Papers List is easier to see the titles, but doesn’t have links.
• 2017 Session List is organized in the order of presentation, but it has links to the “video previews” (25 seconds) that have the abstracts on the pages. The DOI links will take you to the digital library. The 2017 Official Papers List is easier to read, but lacks the links.
• Unofficial Papers Lists (with links to PDFs)
  • 2016 VAST
  • 2016 InfoVis
  • 2016 SciVis

You are not required to read any papers. But, I would like you to look at at least some of the abstracts to papers whose titles you find intriguing (things that you might be interested in enough to want to read), or at least watch a few of the videos (the videos are often not very good).

Optional

This is the closest thing I can find to a survey paper about volume rendering (which is probably the most common case). The front parts cover the basics, but it quickly gets into more detail than you probably want.

• Arie Kaufman and Klaus Mueller. Overview of Volume Rendering. Chapter 7 of The Visualization Handbook (Hansen and Johnson eds), Academic Press, 2005. (chapter7-volumerendering.pdf 0.7mb)

Course evaluations for this class will be done through aefis.

To encourage everyone to do an eval, I will set aside some time at the end of class tomorrow (Wednesday 12/4). This will give everyone a chance to do an evaluation.

For the 11 people who have done evaluations already, thank you! You’ll be able to leave class early tomorrow.

If you don’t come to class, please do the evaluation online on aefis.

Class Meetings

• Mon, Dec 3 – Lecture/ICE:Route Maps, Special Graphs
• Wed, Dec 5 – Lecture:Presentation and Anaimation
• Fri, Dec 7 – No class, but extra office hour 11-noon

Week Deadlines

• Reading: Week 14 – Presentations and Animation (due Mon, Dec 3 – preferably before class)
• There is no Quiz 14
• Online Discussion 14: Presentations (first post due Wed, Dec 5)
• Seek and Find 14: Something Animated (due Fri, Dec 7)
• Design Challenge: DC3:Drafts (due Fri, Dec 7)

Last week we talked about graphs. We didn’t get through everything. I’ll mention some things we didn’t get to at the beginning on Monday, and then we’ll do a design exercise.

The readings for this week are about animations and presentations.

“How to give presentations” is an obviously important topic. There’s a huge irony in talking about how to give a talk. Especially since it makes me realize that in class I often don’t follow my own advice. Read through my notes (see readings below). Watch a Hans Rosling video (see Video Presentations below – but remember, you are not Hans Rosling). Maybe we’ll talk about it an class a bit.

Animation is an interesting topic (and in some ways, how I got started doing Vis). I am not sure how much to say about it.

On Wednesday, we’ll do something in class that connects to these two topics. I haven’t decided what yet. It might be me talking about another topic…

You may want to look at this week’s learning goals Learning Goals 14: Week 14 – Presentation and Animation.

Readings (due Mon, Dec 3 – preferably before class)

Two topics this week, neither with much reading. You need to read a blog posting I made years ago, and watch a few videos.

I’m not sure how much of my rant on presentations I’ll give in class this year. But helping you think about presentations is something I like to do in this class (and all grad classes).

Before reading my notes, here are some caveats (note: this is taken from the 2012 class):

• The goals and standard for presentation really vary across venue/discipline. What we value in computer science (in particular the areas I work in) are quite different than in other disciplines. It’s hard for me to discuss this without value judgement (since I am bred to believe in the “CS way”), but I also plead ignorance to the practices in other area. I’d like to use this as a chance to learn about others.
• I don’t consider myself to be a great presenter. Do as I say, not as I do. The upside of this, is that it means I think about how to be better at it.
• A lecture is not the same as a talk, so what you see in class is quite different than what you would see in one of my talks.
• Even within a particular style/venue/type of talk, there is a wide range of opinions on what is good talk, what the goals should be, …
• The “right answer” depends not only on the situation, but on the person. But that will be one of the biggest lessons I hope you get. I may not speak to your specific case, but hopefully, you can see how the general lessons apply.
• As you might guess, I have strong opinions. But you don’t have to guess at what they are, since I’ve written them down.

Given that…

My real goal is to get you to think about what might make for a good presentation, and to form your own strong opinions – even if they are different than mine.

Given that, read my posting about presentations. Yes, it’s from a 2011 class – but I think if I were updating it, it wouldn’t be much different.

Video Presentations

Hans Rosling is a famous presenter – talking about social issues around the world in venues like TED, etc. He was famous for presenting data in a compelling way to make his points for a broad audience. Sadly, he died this year. But his influence is significant (both on presentating data and on the world in general).

If you haven’t seen a Rosling talk, you need to experience one. If you have seen one, you probably won’t mind watching another.

There are lots of videos of rosling presentations – here’s one I have handy, or here’s another one.

The actual point of Rosling is not his visualizations (he does use standard visualization effectively – often with animation), but rather as a way to talk about presentations.

Animation

Rather than read about animation, I’ll let you watch a (reasonably old video) about it’s role in visualization.

I’ll kill two birds with one stone here: I want you to think about the role of animations in visualization, and how to present research results in video form. So, I’ll have you watch a research video about animation in visualization!

You don’t have to read the paper, but you do have to watch the video:

• Heer, Jeffrey, and George Robertson. “Animated Transitions in Statistical Data Graphics.” IEEE Transactions on Visualization and Computer Graphics 13, no. 6 (January 2007): 1240–47. doi:10.1109/TVCG.2007.70539. (web page with video)

Some of the ideas in the video have been questioned in perceptual studies, but I think the basic concepts are still worthwhile.

Animation (optional)

The classic reference for the Principles of Animation is “The Illusion of Life” – a book about the history of Disney animation. It’s a coffee table art book – not necessarily something meant for either animators or computer scientists to learn from. But it is fabulous, and full of great examples from classic Disney films:

• Johnson and Thomas. Disney Animation: The Illusion of Life. Several editions (Aberville Press, 1981 is the “original” I think). Chapter 3:The Principles of Animation. (Illusion-of-life-3-ChapterThree-Principles.pdf 27.5mb)

John Lasseter was a Disney animator who went to work with a small company of graphics hackers. The company grew and grew and grew and now everyone knows Pixar. His SIGGRAPH 1987 paper was a seminal work where he introduced the graphics world to the principles of animation. The basic content is the same as the Johnson and Thomas chapter, but its more condensed, and the examples are from Pixar films.

+John Lasseter. Principles of traditional animation applied to 3D computer animation. SIGGRAPH 1987. (acm site with PDF). Note, there are many summaries of this paper on the web. Here’s one by a well-known animator. But do read the original. (well, you’re even better off reading a Disney thing first, then reading this for historical context – if you’re interested ).

Our discussion of animation is mainly about to ADDING motion to things, not necessarily visualizing motion. (in which case exageration and staging would be distortions). To get you thinking about showing motion, we’ll think about the opposite problem of animation:

Cutting, J. E. (2002). Representing motion in a static image: constraints and parallels in art, science, and popular culture. Perception, 31(10), 1165-93. [(online)](http://www.perceptionweb.com/abstract.cgi?id=p3318)

To give you a sense of what will happen for the last 2 weeks of the semester…

• We will not have any more quizzes – the topics don’t lend themselves to quizzes, and I expect people want more time with DC3.
• We will not have any more Friday classes. On Friday, December 7th, I will have an office hour 11-noon. (but not Friday, November 30th).
• There are readings, discussions, and seek and finds for the last weeks.
• On Monday, December 3rd, we’ll wrap up talking about graphs with a discussion of things that are better than force-directed layout, and an in class-design exercise (that will really involve doing some designing).
• Sometime in the last 3 classes, we’ll talk about presentations (since people always like to hear about that, and reading about them doesn’t get the point across). We’ll also try to talk about uncertainty, modeling, machine learning, … – a lot to cram in.
• The main thing that is going on will be DC3. At this point, the intermediate deadlines are mainly for us to check that you are making progress.

On the schedule, I had listed Friday 11/30 as an optional class for a discussion of DC3. Since we had a DC3 discussion before Thanksgiving, I have decided not to hold this additional class.

There will be no more Friday classes (there is only 1 more week of Fridays). I will have an extra office hour on Friday Dec 7 (11-noon) to help people with Design Challenge 3.