The Week in Vis 12 (Mon, Nov 18 – Fri, Nov 22): Graphs

by Mike Gleicher on November 15, 2019

Week in Vis 12 Mon, Nov 18-Fri, Nov 22

Last week, we talked about evaluation and wrapped up DC2. That means this week its time for sleep DC3! The DC3 draft is actually on the web, but it’s still a draft – expect an announcement Monday. We’ll talk about it in class on Wednesday.

For DC3 you will be allowed to work with a partner (although, we prefer you pick a partner from another department). If you want help finding a partner, let us know – we can do some match-making. There is nothing due for DC3 on Wednesday, Nov. 20 (other than to tell us if you want to work with a partner).

Note: my office hours are cancelled this week: I will be leaving town after class on Wednesday.

Readings for the Week

Finding appropriate readings is surprisingly hard.

  • Arrange Networks and Trees (Chapter 9 from Munzner’s Visualization Analysis & Design) (Munzner-09-ArrangeNetworks.pdf 0.9mb)
  • has a huge number of visualizations of trees. Look at the pictures and try to get a sense of how many different ways there are to do this.

Tamara Munzner gave a talk that gets across the point that there are many ways to show a graph. It gets the point across that there are lots of design choices and options. Plus, you’ll get a sense of the person behind the book (although, this was almost a decade ago). But, sitting through the hour is a bit much – so it’s OK to just watch a little bit and read through the slides.

  • Tamara Munzner. 15 Views of a Node-Link Graph: An InfoVis Portfolio, Google TechTalks, Mountain View CA, 6/06. Talk video (Video on YouTube) (slides)

I also want you to look through a survey on graph drawing. The “required” reading is the Gibson paper. In 2018, I used the vonLandesberger survey paper (optional, below). This paper is still too big a list of too many things (the paper is over 30 pages long – or 60 pages in the double spaces). I do not expect you to read the whole thing. But, skim through it. If you read the first paragraph of each section, you’ll get a sense of the range of things – and if you want a huge list of specific examples, you can read more.

  • Gibson, H., Faith, J., & Vickers, P. (2013). A survey of two-dimensional graph layout techniques for information visualisation. Information Visualization, 12(3–4), 324–357. (doi) (author verson)


There is a lot out there. One good general source for background is the book “Handbook of graph drawing and visualization” – which you can find drafts of the chapters online. In particular, the Chapter on Force-Directed Layout (at least the beginning parts of it) gives a review of the classical algorithms.

  • Kobourov, S. (2016). Force-Directed Drawing Algorithms. In Handbook of Graph Drawing (pp. 383–408). (pdf online)

For a modern algorithm for small to medium graphs:

  • Dwyer, T. (2009). Scalable, Versatile and Simple Constrained Graph Layout. Computer Graphics Forum, 28(3), 991–998. (pdf) (doi)

    It’s a modern take on graph layout. It considers many aspects about what makes for a good layout, and uses real optimization methods to achieve them. The method gives a sense of the evolution and all the methods that came before it). This might be a little too CS-technical for most people. Don’t worry about the details of the algorithms, but get a sense of the kinds of things the best algorithms try to achieve. In practice, people usually use simpler algorithms (force-directed layout)

I wanted to find a survey paper that covered the more computational aspects (the layout algorithms). I haven’t found one that I like. Instead, I am recommending this paper. Read it to get a sense of what the basic methods are – don’t try to get at all the details and subproblems and …

  • von Landesberger, T., Kuijper, A., Schreck, T., Kohlhammer, J., van Wijk, J. J., Fekete, J.-D., & Fellner, D. W. (2011). Visual Analysis of Large Graphs: State-of-the-Art and Future Research Challenges. Computer Graphics Forum, 30(6). doi:10.1111/j.1467-8659.2011.01898.x (official version) (authors’s copy)

More Feedback on DC1

by Mike Gleicher on November 14, 2019

First: initially, DC1 grades didn’t have the comments. I had to repost them. Hopefully, the comments help you understand your score. Remember, this score is only for the final handin part (see previous post). Your numeric score is the average of the scores the graders gave you. Not everyone was graded by 2 graders.

If you still have questions…

Please do not ask us in (before/after) class! We probably don’t remember your specific assignment.

If you want to come by office hours to discuss, please do. I won’t have office hours on 11/20. I will be leaving town pretty promptly after class. I will have office hours on 11/27 (before Thanksgiving). Aditya can also help you understand your grade (in fact, he might be a better resource).

It’s probably better to discuss things after the final DC1 grades (including peer review) are done.

DC1 Grading

by Mike Gleicher on November 14, 2019

We will soon release the grades (partially) for DC1 – sorry for the delays.

The grades are for the “main handin” – which is not your final DC1 grade. (it is 80% – specified in the assignment).

To get your DC1 grade:

  • add 2 to your “main handin” grade if you did all of the earlier checkpoints – this is a bonus for your patience. (it also makes the statistics match the expectations for the class)
  • the other 20% is for your peer reviews (which we will grade separately)

We’ll get the final grades back to you soon.


DC2 Deadline (today, Nov 13)

by Mike Gleicher on November 13, 2019

As you hopefully know, DC2 is due today, November 13th. (according to the updated schedule).

You’ve had more than 4 weeks, will another day make a difference?

Per class policy, you can turn things in after the deadline. Your penalty will depend on whether this is a one time time, or a chronic problem. (if you’re late with everything, we are more likely to penalize you) We do take into account how late things are as well. And often we can tell an assignment where the extra day was to polish a big effort (or squash one last bug) vs. problematic procrastination.

For this assignment, we will accept late assignments until November 17th. This is what Canvas would have told you. We may penalize you if the assignment is turned in after the 13th.

The main reason to get people to get DC2 done is to have people move on to DC3. But we haven’t posted DC3 yet, so there’s a little less rush for that. I’d recommend that you turn in DC2 on time and take a break before DC3. But it is your choice.

Preparing for DC2 submission

by Aditya Barve on November 11, 2019

Some guidelines are posted on Canvas to help you prepare your DC2 submission. They may also prove useful for future submissions.

Week in Vis 11 Mon, Nov 11-Fri, Nov 15

Last week we talked about color, which is a big enough topic we could have kept talking about it.

This week, we’ll take on the question of evaluation: how do we know if the visualizations we make are good? Part of the idea of the class (and Munzner’s book, which is based on the this idea) is that evaluation is something that needs to be considered early because it provides a lot of insights for design. This year, the “evaluation” week got pushed late (this is week 11), but really, we’ve been talking about it all along (as we think about effectiveness and critique).

DC2 is due this week. DC3 might not be ready, so you might get a bit of a break. We’ll discuss DC3 in class on Wednesday.

Readings for the Week

Evaluation is such a big and hard question. This will get at the key concepts.

  1. Analysis (Chapter 4 from Munzner’s Visualization Analysis & Design) (Munzner-04-Validation.pdf 0.5mb)
  2. The five qualities of great visualizations (Chapter 2 of The Truthful Art) (theTruthfulArtCh2.pdf 10.0mb)
  3. Graphical Integrity (Chapter 2 of Tufte’s The Visual Display of Quantitative Information) (1-VDQI-2-GraphicalIntegrity.pdf 62.2mb)
  4. Chris North, “Visualization Viewpoints: Toward Measuring Visualization Insight”, IEEE Computer Graphics & Applications, 26(3): 6-9, May/June 2006. pdf (doi; 4 pages)This is a good introduction to the challenges of visualization evaluation. And it’s short.
  5. Dragicevic, P., & Jansen, Y. (2018). “Blinded with Science or Informed by Charts? A Replication Study.” IEEE Transactions on Visualization and Computer Graphics, 24(1 (Proceedings InfoVis 2017)), 1–1. DOI PDFI want you to read an empirical paper. I pick this one because it takes quite a simple question and tries to be painstakingly thorough with it. Moreover, it is mainly trying to replicate an experiment that got a lot of press. While the authors didn’t set out to contradict the prior paper, it seems they got a different answer to the same question.


The “Chartjunk” paper would be required reading – except that we’ve already learned about it from Cairo, The Functional Art Chapter 3 (theFunctionalArtCh3.pdf 11.4mb). It’s worth looking at if you’re really interested in the topic. And the Few blog posting may be more valuable than the article itself

  • Bateman, S., Mandryk, R.L., Gutwin, C., Genest, A.M., McDine, D., Brooks, C. 2010. Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts. In ACM Conference on Human Factors in Computing Systems (CHI 2010), Atlanta, GA, USA. 2573-2582. Best paper award. project page w/pdf (doi). (10 pages)This is a pretty provacative paper. You can pick apart the details (and many have), but I think the main ideas are important. There is a ton written about this paper (those of the Tufte religon view this as blasphemy). Stephen Few has a very coherent discussion of it here. In some sense, I’d say it’s as useful than the original paper – but I would really suggest you look at the original first. While more level-headed than most, Few still has an Tufte-ist agenda. Reading the Few article is highly recommended – in some ways, its more interesting than the original.
  • Munzner, T. (2009). A Nested Model for Visualization Design and Validation. IEEE Transactions on Visualization and Computer Graphics, 15(6), 921–928. (pdf) (doi)Chapter 4 of Munzner’s book is based on this earlier paper that was quite influential (at least to my thinking). It is somewhat redundant with what is in the chapter, but for completeness, you might want to see the original.

In case you cannot get enough of Tufte, you can get his ideas on what is good (Ch5) and bad (Ch6).

If you’re wondering whether the deceptions Tufte mentions actually fool people, here’s an empirical study of it:

  • Pandey, A. V., Rall, K., Satterthwaite, M. L., Nov, O., & Bertini, E. (2015). How Deceptive are Deceptive Visualizations?: An Empirical Analysis of Common Distortion Techniques. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems – CHI ’15 (pp. 1469–1478). New York, New York, USA: ACM Press. (doi)

Some other stuff on evaluation:

  • Lam, H., Bertini, E., Isenberg, P., Plaisant, C., & Carpendale, S. (2011). Empirical Studies in Information Visualization: Seven Scenarios. IEEE Transactions on Visualization and Computer Graphics, 18(9), 1520–1536.
  • Correll, M., Alexander, E., Albers Szafir, D., Sarikaya, A., Gleicher, M. (2014). Navigating Reductionism and Holism in Evaluation. In Proceedings of the Fifth Workshop on Beyond Time and Errors Novel Evaluation Methods for Visualization – BELIV ’14 (pp. 23–26). New York, New York, USA: ACM Press. ( happens when I let my students rant.
  • Gleicher, M. (2012). Why ask why? In Proceedings of the 2012 BELIV Workshop on Beyond Time and Errors – Novel Evaluation Methods for Visualization – BELIV ’12 (pp. 1–3). New York, New York, USA: ACM Press. (link)Me ranting about how evaluation shouldn’t be an end unto itself. The workshop talk was much better than what I wrote.
  • You should read at least one of the papers by Michelle Borkin and colleagues on the memorability of visualization. These papers are very provocative, and provoked some people to be downright mean in attacking it. You don’t need to worry about the details – just try to get the essence. The project website has lots of good information.Michelle Borkin et. al. What Makes a Visualization Memorable? pdf InfoVis 2013 (10 pages).
    This is another radical thought of “maybe Tufte-ism isn’t all there is – and we can measure it.” Again, we can quibble with the details, but they really re getting at something real here.

    Michelle Borkin et. al. Beyond Memorability: Visualization Recognition and Recall. InfoVis 2015. (pdf); 10 pages

These are in no particular order…

  • It is good to discuss the pros and cons of your designs.
  • Don’t expect to have a perfect design (there probably isn’t one) – but do articulate the rationale, and the pros and cons.
  • No design is good for all tasks. Describe what it is good for (and why), and what it isn’t good for (and why)
  • Use examples that illustrate things that you can see with your design.
  • Explain the decisions you made – give rationale.
  • Some designs may cover many tasks – some designs may cover few tasks.
  • You may want to have many designs that cover a range of tasks. These might be integrated into a single program and coordinated. Or you might keep them separate.
  • Your designs might require some “non-visualization” components – such as statistical analyses or standard searches. But this shouldn’t be the main thing. There should be some visualization component.
  • Designs shouldn’t be needlessly complex  – simple tasks can have simple designs.
  • Tasks that are too easy will not get good grades. “What are the products with the most reviews” (answered by a simple list – a bar chart isn’t that much better), is not that hard. But it could lead to other things…
  • Putting multiple simple tasks together (a simple question leads to a deeper exploration) can be interesting.
  • Use good encodings and detail choices. Fancy implementations don’t make up for bad design choices.
  • Describe interactions and use cases.
  • Explain tasks and “anti-tasks” (tasks it would not be good at)
  • Talk about scalability – of the design mainly, but also the implementation.
  • If there is an obvious “baseline” design, you might explain why you chose your design instead of it.
  • There are different ways to do well. If you have simpler designs, you can make up for it with more thoughtful discussion and having a wider range of designs (to cover a range of tasks).

The Week in Vis 10 (Mon, Nov 4 – Fri, Nov 8): Color

by Mike Gleicher on November 1, 2019

Week in Vis 10 Mon, Nov 4-Fri, Nov 8

This past week, we got the basics of human perception. This week, we’ll drill a little deeper into a particular aspect of it:  color. The more I learn about color, the more I realize how complicated it is. If nothing else, it is interesting. And important.

The schedule for Design Challenge 2 was changed – you have an extra week. Hopefully, you will use this to make even better projects. We’ll give some hints in the next few days (although we will not be able to provide specific feedback on the sketches/initial signs of life to everyone). You can come to office hours (either for me on Wednesday, or Aditya during Friday class time).

Readings for the Week

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. (PDF from canvas) (originally a web article).

    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 2.8mb)
  3. Map Color and Other Channels (Munzner-10-MapColor.pdf 0.4mb)

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

  4. Borland, D., & Taylor, R. (2007). Rainbow Color Map (Still) Considered Harmful. IEEE Computer Graphics and Applications, 27(2), 14–17. (rainbow-still-considered-harmful.pdf 0.7mb) (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 – optional below) gets at this in a more mathematical way, but it’s overkill for class purposes.

  5. 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. It’s a good fit because it focuses on color. And she’s my former student.

Color: Optional

We’ll talk about Color Brewer in class, but if you want to know the science about it:

  • Cynthia Brewer. Color Use Guidelines for Data Representation. Proceedings of the Section on Statistical Graphics, American Statistical Association, Alexandria VA. pp. 55-60. (web) (Brewer_1999_Color-Use-Guidelines-ASAproc.pdf 1.5mb)

    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!

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

  • 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 4.3mb)

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

  • Chapter 10, Principles of Color (Slocum-principles_of_color_cropped.pdf 8.9mb), 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 (perception-of-color.pdf 19.5mb), 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:

DC2 Schedule (deadline extension)

by Mike Gleicher on October 31, 2019

Short version: The deadline for DC2 has been pushed back a week. It is now due on Wednesday, November 13th.

Longer version: we have been slow at providing people with feedback (both on DC1 as well as the DC2 initial parts). And, realistically, we won’t be able to start looking at the handed in assignments right away. The bigger issue is starting DC3, but for various reasons we will want to delay that as well.


  • The final handin for DC2 is now Wednesday, November 13th. We will be pretty firm with that deadline.
  • If you want feedback, please either come to the “consulting” session on Friday, Nov 1 (during the class period), my office hours on Wednesday the 6th, or office hours that Aditya will post next week)
  • We will not provide feedback on sketches or signs of life – however, we may post some guidelines for good assignments sometime next week.
  • Some people asked to see some examples of good assignments from prior years. I will show some in class on either Nov 4 or Nov 6. The assignments were different last year, but you’ll see how students put together nice implementation with thoughtful discussion and self-critique.

DC2 Help Session / Extra Office Hour

by Mike Gleicher on October 30, 2019

Aditya and I will hold an “extra office hour” on Friday, during class time, in the class room (312 Wendt).

We plan to be there 11-noon (I may need to leave at 11:45).

Our idea is to do 1-on-1 consulting, but if people have similar questions, talk to people en masse. Generally, we find it is useful for such discussions to be public (since we can all learn from each other), but if you want to keep things private, we can.

This is, of course, optional.