ARCHIVED Course Web for the Fall 2017 edition of CS765 Data Visualization

Initial Posting Due: Tue, Nov 14 at (Canvas Link)

Readings

Since this is the “implementation week” of Design Challenge 2, the reading load is light. Also, because while uncertainty is a critical topic, there is no obvious good reading for it. Last year I gave this whole long list.

This year, all you have to read is this short paper:

• Boukhelifa, N., & Duke, D. J. (2009). Uncertainty visualization: why might it fail? In Proceedings of the 27th international conference extended abstracts on Human factors in computing systems – CHI EA ’09 (p. 4051). New York, New York, USA: ACM Press. doi:10.1145/1520340.1520616 (ACM – free access on campus or using UW library proxy).

If you want to read more, I recommend these two:

We wrote a paper that deals with a very common case of uncertainty visualization, and one of the most standard visualizations.

• Correll, M., & Gleicher, M. (2014). Error Bars Considered Harmful: Exploring Alternate Encodings for Mean and Error. IEEE Transactions on Visualization and Computer Graphics, 20(12), 2142–2151. doi:10.1109/TVCG.2014.2346298 (web)

The statisticians have a lot to say about how we should think about uncertainty, especially in experiments. This paper gets at many of the issues (it is statisticians explaining to psychologists what they should do).

• Cumming, G., & Finch, S. (n.d.). Inference by eye: confidence intervals and how to read pictures of data. The American Psychologist, 60(2), 170–80. doi:10.1037/0003-066X.60.2.170 (pdf)

Online Discussion

Initial Posting Due: Tue, Nov 14 at (Canvas Link)

The main thing this week was Design Challenge 2. But there was also the reading about uncertainty. We’ll discuss both.

For your initial posting (due Tuesday): For DC2 we didn’t consider uncertainty in the data. (well, the assignment didn’t discuss it – maybe you are considering it). What kinds of uncertainty might you have in the multi-line series data? What are some possibilities for displaying it? How might you augment the basic designs?

In a second posting: describe what you are doing for DC2. What tasks are you focusing on? Are you running into any issues?

For discussion, you can either discuss the ideas you came up with for displaying uncertainty in DC2 data, or discuss what is going on with DC2.

Initial Posting Due: Tue, Nov 07 at (Canvas Link)

Readings

Note: Since Design Challenge 2 is in high gear, the reading for this week is intentionally a little bit lighter.

The first reading is a survey paper that provides a good way to organize many of the interactions we see in visualization, and provides lots of good examples.

1. Heer, J., & Shneiderman, B. (2012). Interactive dynamics for visual analysis. Communications of the ACM, 55(4), 45. (pdf) (doi)
2. Maniplate View (Chapter 11 from Munzner’s Visualization Analysis & Design) (Munzner-11-ManipulateView.pdf 545 kb)
3. Facet into Multiple Views (Chapter 12 from Munzner’s Visualization Analysis & Design) (Munzner-12-FacetMultipleViews.pdf 1.0 mb)

   This isn’t specific to interaction, but it fits better here than anywhere else.

Optional

I’ll use this paper to frame the discussion in class. It provides a good “why not add interaction” point of view.

• Lam, H. (2008). A Framework of Interaction Costs in Information Visualization. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1149–1156. (doi). (pdf link to Heidi’s page)

Online Discussion

Initial Posting Due: Tue, Nov 07 at (Canvas Link)

Interaction is a great tool for addressing visualization challenges. When there’s something hard, add some interaction to let the user solve the problem.

For this week’s discussion, I want you to consider some of the interactions you see in visualizations and consider why they are necessary.

1. Pick an example (or two) of a a visualization that uses interaction effectively. Describe what the interaction is, and why it’s so important. Describe an alternative design that achieves the same effect without interaction (or why you think it wouldn’t be possible to do without interaction).

2. Pick an example (or make one up) of a visualization that uses interaction where it would be possible to achieve similar effects using a static (non-interactive) visualization. What are the pros and cons of the two different (interaction / non-interaction) approaches.

Hopefully, these examples will give groups a chance to have some discussion about the pros and cons of interaction and the alternatives. You might also discuss how different interactions might have been chosen.

Initial Posting Due: Tue, Oct 31 at (Canvas Link)

Readings

Color is a surprisingly complex topic – and the complexities of perception and display have real impact on how we use it for Vis. There is some redundancy in these readings, but it’s hard for me to choose which ones are best. It’s probably OK to see it multiple ways. This is actually less reading than I’ve given in the past for the topic (see 2015 Color Readings)

1. Maureen Stone. Expert Color Choices for Presenting Data. Web Resource.

   Maureen really is an expert on color. This is a good review of the basics, and then gets into why it’s important to get it right, and how to do it.

2. Color (Chapter 4 of Visual Thinking for Design) (Ware-4-Color.pdf 2.8 mb)

3. Map Color and Other Channels (Chapter 10 from Munzner’s Visualization Analysis & Design) (Munzner-10-MapColor.pdf 356 kb)

   Color is really 10-10.3, 10.4 talks about other channels. It’s a good reminder.

4. Borland, D., & Taylor Ii, R. (2007). Rainbow Color Map (Still) Considered Harmful. IEEE Computer Graphics and Applications, 27(2), 14–17. (pdf on Canvas) (doi)

   The rainbow color map is still used (10 years after this paper). Understanding why you shouldn’t use it is a good way to check your understanding of color ramp design. Breaking that rule (and using it effectively) is a more advanced topic. Most uses of rainbows are ineffective.

   A more recent paper (Bujack et. al below) gets at this in a more mathematical way, but it’s overkill for class purposes.

5. Cynthia Brewer. Color Use Guidelines for Data Representation. Proceedings of the Section on Statistical Graphics, American Statistical Association, Alexandria VA. pp. 55-60. (web) (Canvas)

   The actual paper isn’t so important – it’s the guidelines she used in creating Color Brewer, which also tells us how to use it. What is more important is to actually check out ColorBrewer which is a web tool that gives you color maps. Understand how to pick color maps with it, and try to get a sense of why they are good.

   The irony is that this, one of the most important papers about color, wasn’t printed in color!

Optional

If you want a little more of how color science and vis come together.

• Danielle Albers Szafir. “Modeling Color Difference for Visualization Design.” IEEE Transactions on Visualization and Computer Graphics, 2018. In the Proceedings of the 2017 IEEE VIS Conference. (best paper award winner).

  This paper is really practical in that it shows how color science and modeling and be used to tell us what will and won’t work in visualization. It shows the value in careful experimentation and modeling.

• Bujack, R., Turton, T. L., Samsel, F., Ware, C., Rogers, D. H., & Ahrens, J. (2017). The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps. IEEE Transactions on Visualization and Computer Graphics, 24(1 (Proceedings SciVis)). (doi)

  This paper does a serious, deep dive into figuring out what makes a good or bad color ramp and making the intuitions mathematical. You can play with their tool for assessing color ramps.

In case you want a few other perspectives on color…

• Color and Information (Tufte’s Chapter 5 of Envisioning Information)(2-EI-5-ColorandInformation-small.pdf 4.3 mb) (2-EI-5-ColorandInformation.pdf 55.4 mb)

  Tufte is famously anti-color, except when he isn’t.

• Chapter 10, Principles of Color (Canvas), from Thematic Cartography and Geographic Visualization, 2nd edition by Slocum et. al.

  This is from a cartography (map making) textbook – but it’s a great intro since it gets into some of the technical issues of reproduction.

• Chapter 5, The Perception of Color (Canvas), from Sensing and Perception (a psychology of perception book).

  As you might expect, a Psychology textbook will give you even more about the science of color. It’s probably more of the perceptual science than you want, unless you’re a perceptual science researcher in which case you may have read it already.

• Here are some postings from a design blog that give a nice tutorial that is a little more design oriented:

  • Color Theory for Designers, Part 1: The Meaning of Color
  • [Color Theory for Designers, Part 2: Understanding Concepts and Terminology] (http://www.smashingmagazine.com/2010/02/02/color-theory-for-designers-part-2-understanding-concepts-and-terminology/)

For something different, here are some papers that show why it is important to use color correctly:

• Borkin, M. A., Gajos, K. Z., Peters, A., Mitsouras, D., Melchionna, S., Rybicki, F. J., … Pfister, H. (2011). Evaluation of artery visualizations for heart disease diagnosis. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2479–88. (pdf) (doi)

Online Discussion

Initial Posting Due: Tue, Oct 31 at (Canvas Link)

With color, there are so many different aspects to talk about. It’s hard to know how to phrase a question to get you to think about it broadly. So instead, I’ll ask a general question and a second question that is meant to get you playing around.

1. There are all sorts of different issues in color… perception, semantics, reproduction, … How should these influence how we use color in visualizations? How can we make good choices about when and where to use colors, and which colors to use when we do?

2. Go to ColorBrewer and pick out a favorite ramp. Why do you like it? What would it be good for? Why is it so good for this purpose? You may also try to make a pallete using Colorgorical and do the same thing.

Initial Posting Due: Tue, Oct 24 at (Canvas Link)

Readings

The main readings are the Ware chapters, since it’s a good introduction to the basics of perception, and its impact on design. Chapter 6 of Cairo is useful because it considers “higher level” perceptual issues. I also include Cairo Chapter 5 (as optional) because it’s redundant with Ware, but it’s fun to see his (less scientific) take on it.

I also want you to look at the Healy and Enns paper / resources. It is sufficient to look at the web survey (since it has the cool demos).

1. Visual Queries (Chapter 1 of Visual Thinking for Design) (Ware-1-VisualQueries.pdf 2.5 mb)
2. What We Can Easily See (Chapter 2 of Visual Thinking for Design) (Ware-2-EasilySee.pdf 2.1 mb)
3. Structuring Two Dimensional Space (Chapter 3 of Visual Thinking for Design) (Ware-3-StructuringSpace.pdf 2.6 mb)
4. The Eye and Visual Brain (Chapter 5 of The Functional Art) (theFunctionalArtCh5.pdf 5.4 mb) Optional – but I listed it here to keep it in order
5. Visualizing for the Mind (Chapter 6 of The Functional Art) (theFunctionalArtCh6.pdf 8.1 mb)
6. Healey, C. G., & Enns, J. T. (2012). Attention and Visual Memory in Visualization and Computer Graphics. IEEE Transactions on Visualization and Computer Graphics, 18(7), 1170–1188. (pdf) (doi)

   Warning: this survey is a little dense, but it gets the concepts across with examples. Don’t worry about the theory so much. Get a sense of what the visual system does (through the figures, and the descriptions of the phenomena), and skip over the theories of how it does it (unless you’re interested).
   There is an older, online version as Chris Healy’s web survey which has lots of cool pre-attention demos. But the text in the paper is much better, and the paper includes more things.

Optional

Perceptual science is a whole field, so we’re just touching the surface. Even just the beginnings of what is relevant to visualization.

• Franconeri, S. L. (2013). The Nature and Status of Visual Resources. In D. Reisberg (Ed.), The Oxford Handbook of Cognitive Psychology (pp. 1–16). Oxford University Press. (pdf) (doi)

  This is a survey, similar to Healey and Enns above, but written more from the psychology side. The first part, where he characterizes the various kinds of limitations on our visual system is something I’ve found really valuable. The latter parts, where he discusses some of the current theories for why these limitations happen is interesting (to me), but less directly relevant to visualization (since it is mainly trying to explain limits that we need to work around). I think these explanations may lead to new ideas for visualization – but its less direct of a path.

• Albers, D., Correll, M., Gleicher, M., & Franconeri, S. (2014). Ensemble Processing of Color and Shape: Beyond Mean Judgments. Journal of Vision, 14(10), 1056–1056. (paper page) (doi)

  We (Steve, myself, and some of our students) have written a survey paper on some other things the visual system can do (and why it can matter for vis). We call it “visual aggregation” and in psychology they call it “ensemble encoding.” It might be useful to skim through for the pictures and diagrams. I will talk about this stuff (at least the work that we did) in class.

• Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design. Jeffrey Heer, Michael Bostock ACM Human Factors in Computing Systems (CHI), 203–212, 2010 PDF (607.4 KB) | Best Paper Nominee

  I mentioned this paper before as a modern version of Cleveland and McGill. It’s interesting to look at these things and think of how the perceptual system causes the effects that we see. Could you predict the results of these experiments based on perception facts?
  It’s also interesting to contrast the experiments we do in visualization to those done by perceptual psychologists (who have different goals).

Online Discussion

Initial Posting Due: Tue, Oct 24 at (Canvas Link)

This week, the readings should (hopefully) give you a crash course in how visual perception works. Rather than just quizzing you to make sure you’ve read and learned about all the visual phenomena, I want to provoke you to think about and discuss how these facts about perception might influence what we do as designers.

For your two required postings:

1. Give some examples of where the way the visual system works gives rise to efficiencies (or inefficiencies) in what we can see easily and describe how this might influence your choices in designing a visualization.

2. Give some specific examples from visualizations where a visual perception concept is utilized (or was failed to be considered, leading to a less desirable result)

There should be enough things here to lead to some conversation.