As we discussed in class today…
I have created a Canvas Discussion for students to discuss aspects of design challenge 1. Feel free to ask questions about a data set, share hints about a tool, or anything else you feel is appropriate.
Week 5 (Mon, Oct 2-Fri, Oct 6) – Design School / Research
- Mon, Oct 2 : No Class: VisWeek
- Wed, Oct 4 : No Class: VisWeek
- Fri, Oct 6 : No Class: VisWeek
- Reading: Week 5 – Design School / Research
- Discussion 5: Visualization Research (first post due 10/03)
- Seek and Find 5: Design Principles (Design School) (due 10/06)
- Design Challenge : Design School – Redesign (due 10/08)
This past week, we looked closely at encodings and practiced trying to pick them apart and redesign them. We also spend a little time talking about graphic design. Hopefully, you got started on Design Challenge 1.
Next week, we’ll break the flow a little bit… No classes (since it’s the IEEE Vis conference). No milestone for the Design Challenge. But there are readings, a seek and find, and an assignment due on Sunday (as a Design Challenge would have been).
There are two disjoint topics: One is to learn about design by picking up some principles, and seeing how to apply them. Another is to get a sense of what visualization research is. The reading/discussion assignments and seek and find should get you doing this – even though there are no lectures to discuss it.
Learning Goals (for this week)
These two topics are put together because of the timing of my travel week. Me being at the Vis conference is an excuse to get students to see what it is.
Design School:
- Give students some appreciation for (and awareness of) visual design principles
- Give students some practice at applying visual design principles
- Give students soem practice at critiquing visual designs
Research:
- Have a sense of the range of topics that are covered at a modern visualization research conference (as a proxy for the topics considered in the field).
- Have an idea of what visualization research papers look like.
This class now has a grader who is helping me with the grading. He is the one going through the assignments.
If you have a question about grading, please ask me (the instructor) and I will pass the question on to the grader.
Also: because of the way Canvas works, your grades go directly to you. We cannot grade everyone, check the grading, and then release the grades. This means that things haven’t always been double-checked before you get to see them.
The class now has a grader! So someone (other than me) will be grading assignments.
A note on the first assignments: we are aware that if you joined the class late, it wasn’t sensible for you to comment on other people. When we graded, we didn’t consider lateness, so we didn’t factor this in. So, you got the score you would have gotten on a future assignment if you did the same thing. At the end of the semester, we will ignore whether assignment 1 was late, etc.
Remember: we grade your assignments on a 3 point scale. We do not factor in lateness. If an assignment is late, we keep track of it, and will look at lateness “statistically” at the end.
This came up in class today, after class today, and in other conversations, so I thought I’d mention it. I tried to make this point in the lecture, but probably wasn’t clear enough.
There are many ways to think about task abstraction. What Munzner gives us in her book is just one way. One thing that the book chapter doesn’t do as well as the paper (that the book chapter is based on) is to give the perspective that there are many other task taxonomies and ideas on how to do task abstraction out there.
The taxonomy that Munzner presents in the chapter makes it seem like all tasks fall neatly into the nice little boxes (categories), and that those category names are something fundamental. I wish it were that simple. There are many ways to divide up the world of tasks. And each way has its good points and bad points.
So don’t get stuck on trying to figure out all of Munzner’s categories, or try to shoehorn any real task into exactly one of the boxes. View them more as food for thought. Sometimes it is useful to know if someone is trying to “enjoy” their data (as opposed to hating it?). Sometimes it is useful to distinguish browsing from exploring – not that the words are important, but that the idea that the viewer may or may not know where to look can be relevant.
Yes, even I have gotten into the “defining a different way to abstract tasks” game. If you’re curious, it’s part of my recent paper on comparisons.
Week 4 (Mon, Sep 25-Fri, Sep 29) – Encodings
- Mon, Sep 25 : Class: Encodings
- Wed, Sep 27 : Class (ICE): Redesign
- Fri, Sep 29 : Class: DCHelp & Vis Practice
- Reading: Week 4 – Encodings
- Discussion 4: Encodings (first post due 09/26)
- Seek and Find 4: Name that Encoding! (and change it) (due 09/29)
- Design Challenge : DC1 – Sketches (due 10/01)
This past week we looked at abstraction – of both data and task – as a way to analyze visualizations, and as a way to analyze problems to try to map them to visualizations. We also played with Tableau a little bit, both as a way to show how abstraction to encoding mappings can work, but also to see it as a tool you might want to try to use for DC1. On Friday, you had the opportunity to bring your own data set for DC1.
This coming week, we’ll look at encodings more carefully. We’ve already been talking about them, but in the readings and class discussions we’ll try to dig a little deeper into what makes for a good encoding, what choices are available for encodings, and why we might want to prefer one encoding over another. In Wednesday’s class, we’ll try another in-class design exercise (bring color pencils/pens).
For this week, Friday is not optional – we’ll use it as a way to talk about Visualization research. And in particular my visualization research (I’ll use it as a chance to plan my talk at the Vis conference the next week).
The following week (October 2-6), there are no class meetings – but everything else will happen (Reading, Discussion, Seek and Find, Design Assignment).
Learning Goals (for this week)
- Appreciate encodings as the building blocks of visualizations, and see how they are put together to make visualizations.
- Know the range of different encoding choices (the visual variables)
- Have a sense of what each visual variable is/is not good for
- Understand how visualizations can be assembled from (and analyzed into) encoding choices.
- Assess standard designs in terms of their encodings and data abstractions
- Appreciate the need for ways to make good choices about encodings
- (probably not time to get to it) See how glyph design is a good testbed for putting encodings together.
Since it was optional and some people didn’t come…
We approved a number of new data sets for Design Challenge 1. You can see them on the list.
We talked a bit about the spirit and requirements for DC1. Nothing that changed the assignment at all.
There was a discussion of how the assignment related to what we’ve learned in class (I’ll argue it does). Which lead to a potentially more interesting discussion of Task Abstraction (the most interesting was actually after class with 2 students). I will probably make a posting about it later.
Short version: If you use a laptop (or other device) in class, please be mindful that you may be distracting others.
There are many very legitimate reasons that people use laptops and tablets in class.
However, screen can be really distracting to the people around you. All those things designed to catch your eye are also catching the attention of others. In fact, some of the readings might help you appreciate this. Much web content is designed to attract the human eye. Whether it is on your screen or someone else’s. Things like bright colors and motion are particularly hard to avoid since the visual system is very sensitive to them in the periphery.
And, if you’re doing something that is not class related, that makes matters worse. It’s one thing for you to decide that you want to be distracted. But if you’re preventing others from learning by distracting them, that’s really bad.
I don’t want to try to restrict what people do, or even define what “legitimate class related use” is. But, I do ask that people try to avoid doing things that may be distracting to others. And generally be thoughtful about the people around you. They can see your screen. They can see your reactions to what is on your screen.
If this continues to be a problem, I will take some action. But for now, I am hoping that making people aware of the problem will improve the situation.
Can you use Excel to do Data Analysis for non-trivial things?(like DC1)
Yes, actually. Even more if you learn some of its fancier features.
Last year, Alper (who was TA) gave in class tutorials on how to do data analysis and vis with excel and Tableau. He is much better with those tools than I’ll ever be.
He wrote up the guide for excel. It specifically designed to help students in this class for DC1. It was meant for the in-class demo, but it is useful on their own. I find it really interesting to see some of the things that can be done easily in excel.