(readings due Tuesday, 3/16)
(note: this was updated on 3/9 based on feedback from the previous readings)
Here, we’ll dig a little deeper into actually using color for visualization.
(0) Charles Poynton has an excellent “FAQ on Color” – it’s a bit technical, and there is a lot of video specific stuff. But its the best place to learn about concepts like Color Temperature. It might help you understand why XYZ and xyY and LAB are all different.
(1) Cynthia Brewer’s work is a common standard for choosing color sets where you want a sequence of distinct colors (as opposed to continuous ramps). You should play with the ColorBrewer tool to see some of the set suggestions (and use it when you need a set of colors). You should read either a brief explanation or a paper.
(2) One thing that you might want to do is use color to display a continuous variable. Here is a paper (a bit old) where Colin Ware explains some issues:
- Colin Ware. Color Sequences for Univariate Maps: Theory, Experiments and Principles. IEEE CG&A, September 1988. (pdf here on Colin’s site – the official versions don’t have color!).
(3) Note that the result here is contrary to what people say (he finds the rainbow map is good). Here’s some arguments to the contrary:
- Borland and Taylor. Rainbow Color Map (still) Considered Harmful. IEEE CG&A, March 2007. (ieee page)
(4) Here are two recent technical articles about details of using color:
(5) Here’s a designer’s take on what colors mean:
This order is not random, but is not necessarily the order you need to look at them.
What you need to do:
Look over #0 – especially if the concepts from the first readings were confusing. Reading #3 (rainbow color maps) is required. You should look at some of #1 (at least the web page, some reading). Take a quick glance at #5 – its quick and fun. Read over at least one of #4 – don’t worry about the details (unless you want to), but try to get an idea of the issues involved. And then look over #2 (to whatever depth you want)
And in the comment mention: what you read, and any insights you got from looking at color from all of these different perspectives.
(due Tuesday, March 10)
Color is a big enough topic that we’ll probably want to spend more than 1 day on it. I’m planning at least 2. For the first color discussion, we’ll have two readings: one on the use of color, the other on some more technical issues.
Chapter 4 of Colin Ware’s Visual Thinking for Design (we’re working through it in order)
Representing Colors as Three Numbers by Maureen Stone. This appeared in IEEE Computer Graphics and Applications, and is a nice summary of the science of color (much better than the chapter of the 559 textbook).
As usual, post a comment indicating that you’ve read these. One thing to think about: how do the technical issues (described by Stone) connect to the design issues (described by Ware).
Here is a simple example of a trajectory (an evolution of the group).
In each case, we start out with things in 2 groups, and the nodes reconnect into 3 groups. There are 3 intermediate steps.
I have generated this data for two different network sizes (12 and 18).
To make things easier, I have not permuted the groups when things are divided into 3 (so, the groups are [0,1,2,3] [4,5,6,7] [8,9,10,11]). But I have also included cases where everything is permuted.
The file naming convention is: bg18pn_000_100.csv which means:
- 18 = 18 node network
- pn = start (2 groups) is permuted, end (3 groups) is not permuted (pp=both beginning and end are permuted)
- 0% of the start
- 100% of the end
Big ZIP of n=12,18,24, with and without permuted ends: bg.zip
Here is the example I used to test my programs with.
There are 3 different “network configurations” (described in terms of cocktail parties of N people):
- There is a single host, that everyone knows. Everyone one also knows their two “neighbors” going around the circle.
- The party has 2 cliques (each of size N/2), each clique is like the first case.
- The same as the second configuration, except that each “non-host” also knows the corresponding person in the other clique.
Here are the three matrices for 3 different sized parties:
If you want all 9 files in one ZIP, download this.
In light of Mike G’s talk on Tue at the Physics dept., the following article from NYT today is very relevant.
This week’s lectures were conversations about low-level perception.
Mike’s Notes: 10-02-23-Perception101.pdf
The first week in March will be centered around the Design Challenge. But on Tuesday, we’ll keep working through Colin Ware’s Book.
- Tuesday (3/2) – We’ll discuss mid-level vision and layout – the reading assignment is Chapter 3 of Visual Thinking for Design. You need to comment on the reading before class. We’ll probably use some of class time for groups to interact.
- Thursday (3/4) – We’ll look at the initial solutions to the Design Challenge. Each group will get (approximately) 10 minutes to present their solutions. The domain experts will be there to discuss. We’ll have a projector (and my laptop if you want to bring things on a USB stick or the web – or you can bring your own laptop). Remember to post a description of your initial solution(s) before class. More details about the mechanics of the Design Challenge will be made available as we figure them out.
For Tuesday, March 2nd, the Reading is Chapter 3 of Visual Thinking for Design.
This week, the reading is intentionally light so you can be more focused on the Design Challenge.
Before 8am on the 2nd, please make a comment about this Chapter as a comment to this posting to help structure our conversation in class.
When we talk about colors and color harmonies, its often hard to see what kinds of things pros use to create their images. This is a really interesting visualization of the color palettes used in ads. The images are pretty striking: Lucious (by Viegas and Wattenberg).
Some of you have asked about what are the “expectations” for what you will create for the design challenge.
I have one very elegant solution to the design problem, but implementing the
idea may take longer than 4th March deadline. What is your expectation
in this work?
Clearly, it is easy to come up with designs that are too hard to implement. Indeed, its probably possible to come up with designs that are too much effort to really be worthwhile for the problem.
If you have an idea, you should try to prototype it. Prototype can have a wide range of meanings. From very “low fidelity” prototypes, to detailed implementations. If you have an idea that would be really hard to implement, maybe you’ll want to prototype it first using some simple mockup – pencil and paper sketches, or a storyboard of pictures of what it would look like. For other ideas, it might be practical to get an implementation such that you can try it out on real data.
There is a tradeoff: on one hand, its nice to have more ideas than you can implement, or fancier ideas than you can implement. On the other hand, there’s a lot to be said for being able to try your ideas on real data. There’s also something to be said for ideas that are easy to implement: if you have an otherwise awesome design that would be too time consuming (costly) to implement, in practice, that might be less useful than something that is more practical.
For March 4th, your focus should be on having ideas your ideas in a form that you can convey to the domain experts for feedback. It is more compelling if they can see things on real data (and “real” simulated data). But it might be just as (or more) compelling if you have a totally amazing design that you explain with pictures and good arguments.
My hope is that each group will do a lot of thinking and designing, and at least a little bit of implementing.