547 Structure

Overview

This course will cover the computer-based visual representation of abstract data sets, designed to help people perform some task more faster or more effectively. In many cases these representations are interactive.

Audience

Strong English communication skills are important for success in this course: there are substantial reading, writing, discussion, and presentation components in the required work.
There are no enforced prerequisites. Grad students from other departments are very welcome: it's even possible to for students in other disciplines to take this course without a programming background, by picking an analysis or survey project.
Either or both of HCI (human-computer interaction) and computer graphics are very helpful but not required.
Past experience shows that you must have strength in at least one of programming, English, or HCI. Students with weak backgrounds in all three have typically not succeeded in previous years.
For undergrads, the new 4th year undergrad visualization course in January 2020 is probably a better match; D3 will be explicitly taught and a programming background is required.
This graduate course does not teach visualization libraries: most students will pick up D3 (Javascript), ggplot (R), or python-based visualization tooling on their own.
Although the class is officially full, don't worry if you can't register: do show up for the first day anyway. In grad CS classes there is typically churn in the first few weeks as people shop around, so it's highly likely that you'll be able to get in. I will give priority to people who have been attending all along.
I'm open to unofficial auditors, there are usually a few each year. You'll get out what you put in: please do the reading for that day, so that you can participate in the in-class discussions. It's OK to come for the first several weeks and then stop if you get too busy with other things.

Number change

In 2014 this course was renumbered to the more sensible "547: Information Visualization" rather than "533C: Special Topics in Graphics: Information Visualization". It is now in the interdisciplinary category rather than the graphics category for PhD breadth purposes. These changes were long overdue, and more accurately reflect the course content.

Structure

For required readings, you submit comments on the readings by 10am Tue, and responses to your classmates comments by 60 min before the afternoon lecture (1pm Tue); you might use those questions as the springboard when there is in-class discussion. Depending on the final number of students who take the course, there ~~may~~ will be individual presentations on a research paper that I assign to you based on a topic of your choice.

Final breakdown of course marks will depend on whether presentations are feasible; rough guidelines are

50% Project
- 15% Final Presentation
- 25% Final Report
- 60% Content
- (20% Intermediate Milestones: pass/fail, penalty only if not submitted/acceptable)
  - Pitch, Proposal, Peer Reviews 1 & 2
20% Presentations
- 75% Content: Summary 50%, Analysis 25%, Critique 25%
- 25% Delivery: Presentation Style 50%, Slide Quality 50%
30% Participation
- 60% Written Questions
- 40% In-Class Discussion/Participation

There will be no final examination in this course, final project presentations will be one afternoon during the final exams period (Tue Dec 12 afternoon, 1-5pm).

In many cases I'll be bucket-sorting individual subcomponents of your grade based on on a scale roughly following {great 100%, good 89%, ok 78%, poor 67%, zero 0%}, although the exact weighting may vary. Note that poor is not a passing mark in a graduate class.

Participation

Students must do the core readings before the lectures and are expected to participate in class: with in-class exercises and group work, project critiques, discussions about the main readings, and discussions following student presentations (if they happen this year). The in-class group work (design exercises, project critiques) is mandatory, and is marked on a pass/fail basis; if you participate and you're engaged, you will pass. Your mark for the level of contribution to the class discussion will depend on both your level of engagement (amount of participation) and the thoughtfulness of your remarks.

By 10am the morning of class (Tue), you must have posted your comments to the Canvas discussion board. You must submit one comment about each reading; a typical week will have four readings. By 60 min before class (1pm Tue) you must submit at least ~~two~~ ONE responses to a classmate's comments; you will be able to see those comments only after you've posted your own. For marking I'll start with pass/fail, I may fall back on explicit marking if I see quality issues.

Please do bring a laptop or tablet to class for use in the in-class exercises, if possible. A smartphone with a camera is also helpful. If you don't have one, then bring a hardcopy printout of your comments with you to class, so you can use them as a springboard for discussion.

I expect you to attend class. If you must miss class you should send me email with an explanation; this email should be in advance not after the fact, unless the problem is illness or emergency. In this case, you may send your questions to me via email, but you will only be given credit if they arrive by usual time on the day of class.

Your submitted comments should be thoughtful, and clearly show that you've done the reading and reflected on it. They may either be phrased in the form of an observation or a question. If you genuinely are confused by some aspect of the reading, then it's useful and legitimate to ask for clarification. However, simply asking something that you could trivially look up yourself is not a good question. Neither are vague statements like "I liked it" or "I learned a lot", or anything that you could write without having thought carefully about the reading. As with any written work that you hand in, I expect correct grammar and spelling. Do be concise: aim for between a few sentences and a paragraph for each reading.

Below are examples of graded comments from a Navigation/Zooming reading in a previous course, ranging from great to poor.

Great
- I'm curious as to what would have happened if the authors had simply preselected the values of the free parameters for the participants in their user study, and then had the users compare their technique to the standard magnification tools present in a 'normal' application (much like the space-scale folks did). Could it be that the users are `manufacturing' a large standard deviation in the free parameter specifications by settling for values that merely produce a local improvement in their ability to manipulate the interface, instead of actively searching for an optimal valuation scheme?
- In a related vein, the speed-dependent automatic zooming met with mixed success on some applications. Isn't this success related to how "compressible" some information is? i.e. because zooming must necessarily throw out some information, it isn't obvious which information to keep around to preserve the navigable structure.
Good
- It would be interesting to compare the approach in this paper to some other less-mathematically-thought-out zoom and pan solutions to see if it is really better. Sometimes "faking it" is perceived to be just as good (or better) by users.
- The space-scale diagrams provided a clear intuition of why zooming out, panning then zooming in is a superior navigation technique. However, I found the diagram too cumbersome for practical use, especially for objects with zoom-dependent representations (Figure 11).
OK
- This seems like something fun to play around with, are there any real implementations of this? Has a good application for this type of zooming been found? Is there still a real need for this now that scroll wheels have become prevailent and most people don't even use the scroll bar anymore?
- Playing with the applet, I find I like half of their approach. It's nice to zoom out as my scroll speed increases, but then I don't like the automatic zoom in when I stop scrolling. Searching the overview I found the location I wanted, but while I paused and looked at the overview, I fell back in to the closeup. I think they need to significantly dampen their curve.
Poor
- Well, what exactly Pad++ is? Is it a progarmming library or a set of API or a programming language? how can we use it in our systems, for xample may be programming in TCL or OpenGL may be ?
- I learned some from this paper and got some ideas of my project.

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Tamara Munzner

Last modified: Fri Dec 29 17:57:41 PST 2017