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Color Tools

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Information Visualization: Applied Perception

Université de New York, Tandon School of Engineering

4.8 (41 notes) | 1.3K étudiants inscrits

Cours 2 de 4 dans Visualisation d'informations Spécialisation

This module aims at introducing fundamental concepts of visual perception applied to information visualization. These concepts help the student ideate and evaluate visualization designs in terms of how well they leverage the capabilities of the human perceptual machinery.

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Avis

4.8 (41 notes)

5 stars
35 ratings
4 stars
6 ratings

RB

Mar 27, 2019

Excellent course for someone who is getting into data visualisation or business intelligence tools. Very well curated for the best of learning experience. Thanks a lot to Enrico Bertini and others!

TA

Nov 13, 2018

Great course with essential material! The content is presented in a very thorough and engaging way by Bertini.

À partir de la leçon

Using Color in Visualization

Using Color in Visualization6:14

Quantitative Color Scales5:54

Multi-hue Sequential Scales6:37

Categorical Color Scales Part 17:37

Categorical Color Scales Part 27:26

Diverging Color Scales7:59

Using Color to Highlight & Emphasize6:21

Perceptual Issues With Color12:16

Effect of Size4:11

Contrast Effects4:18

Luminance for Contrast3:36

Background and Perception5:38

Color Tools11:46

Enseigné par

Enrico Bertini
Associate Professor
Cristian Felix
PhD. Candidate

Transcription

Okay, I want to conclude this lesson by talking about some existing color tools.

Why do I talk about that?

Well, I think it's important for you to know that in the large

majority of cases when you are creating new visualizations,

not necessarily you have to design a new color scheme.

That would be a daunting cause, fortunately,

there are lots of existing tools out there that if

pre-existing color schemes or color pallets.

And you can just use them, and as long as you know how to use

these color scales appropriately, you will be creating effective visualizations.

Of course, all the guidelines that I provided to you so

far will be very, very useful in choosing the right color scheme.

And also in where available also tuning the parameters,

if there are parameters that are available in these tools.

So as a general rule, I would say don't design new

color schemes or color scale if you do not have to.

Because there are very knowledgeable people

out there who've been designing these color schemes for you once for all.

And unless you have a very specific need,

you shouldn't try to create new color scales.

So keep in mind, you still have to make sure that you use these

color tools in the right way, okay?

And again, all the guidelines that I provided so far are very, very important.

Now I want to introduce probably the most famous and

also probably useful, color tool available for visualization.

This tool is called ColorBrewer, and it's been created

originally by Cynthia Brewer who is a professor at Penn State.

And the idea of this tool is to help people understand how color works and

how to use it in specifically in cartography, but

more in general in data visualization.

So what I'm going to do next is to show you how ColorBrewer works.

And how you can use it to better understand how color works and

also what color pallets to use.

Before I do that, let me tell you that a very interesting aspect

of ColorBrewer is that since it's so famous and so effective.

The color palettes that have been regionally created for ColorBrewer,

have been reimplemented and use in many other tools and libraries.

So this means for instance that if you are designing a new visualization and

you are using library like in an API like D3JS.

Which is particularly popular, you will find in the libraries

methods to use the color palettes that have been designed in ColorBrewer.

And this is true for many other tools.

Okay, let's switch to the demo.

What you see here is what our ColorBrewer looks like when you open it for

the first time.

What do you see?

So there are a number of options in the control panel on the left.

And what you see on the right is a sort of simulation

of how the currently selected color scheme looks like,

when used to visualize data on a map.

And you also see, in particular, how color looks like in large areas.

Then large areas where there is one element that is different

inside the area, like here, here or here.

And also, it looks like when you have regions that

contains a lot of different colors, scattered colors,

rather than large areas like this one.

Okay, let's take a look at the control panel on the left.

So the first thing you can do is to select the number of classes.

So right now, there are three different

classes but you can choose 4,

5, 6, 7 up to 12, okay?

So as you can see, as I change the number of classes,

the number of colors available changes in the view on the right.

So let me set these back to 5.

Okay, so the second thing you can do is to generate or ask for

data that is sequential, diverging, or qualitative.

Right now it's sequential, let's take a look at diverging.

So when I click on diverging, you see that the color schemes that are selected and

available change into diverging color schemes.

And when I click on qualitative, there are color schemes that have been

designed to be effective with qualitative data.

Now for each of these cases, ColorBrewer presents

a number of different color schemes at the bottom.

So for sequential, we have multi-hue color schemes,

multi-hue means that there are two hues that are interpolated

between the end of the scale and single hue color scales.

And by now, you should know what this means, okay?

Note that these color schemes have been designed to be perceptually uniform, okay?

So if we increase this to say 8, we have more colors available.

And these colors, again,

have been designed to be perceived uniformly, linearly.

Let's take a look at the diverging color scale.

In the diverging color scale, again, we have the same method that I

presented earlier in this lesson and there are different options.

So say from blue to red, and then we are from green to purple and

we are from green to brown, okay?

And the last one is qualitative.

And here, again, we have different options.

One interesting aspect of the qualitative color scales

is that there are different options in terms of color saturation.

So here, we have highly saturated colors, and here,

we have colors with very low saturation, okay?

What else can you do in ColorBrewer?

Well, you can ask ColorBrewer to show you

only color schemes that are color blind safe.

So if I click here, you can see that ColorBrewer shows you.

So in this case is actually none of them.

Let me change this, so you have to reduce the number of colors back to 4.

So color blind safe, so ColorBrewer with four classes.

It shows you that only one color scheme can

be used and to be color blind safe, okay?

Finally, you can also add on the map some context to see how much

contrast there is between these elements in the background of the map.

For instance, you can add roads and if you want you can also

change the color of these roads, you can add city names and so on.

You can remove or add borders, so you can do a number of things

to understand how color affects the perception of different layers.

Finally, you can also play with the background.

You can have a solid color, or you can have some terrain, and you can also

change the level of transparency between the map and the background.

Last but not least, for a given color scheme,

you can also choose to export the current color scheme

to different tools which is also practically very, very useful.

Okay, this concludes the lesson on color usage.

To recap, we covered quite a number

of different aspects related to how to use color.

So first of all, we discussed the idea that there are three main color uses.

The first one is using color to

communicate information about quantity or magnitude and sequence.

The second one is using color to label

data according to a number of different categories.

The third one is using color to highlight some elements that are important.

And to basically direct the reader's attention to something that

should be highlighted and should attract the reader's attention.

Then we went through a number of specific issues that

need to be taken into account when using the color in visualization.

So for instance,

we talked about the problem of color blindness which is very important.

We talked about the effect of size and how size inteacts with color.

We talked about the effect of contrast and how to take care of contrast.

So this concludes this part of the course,

and it's very important for

you to keep in mind what the guidelines are.

And also to keep in mind that these guidelines can be used both

to create new color schemes, which is particularly hard.

But more practically, to decide among all the available

color schemes that someone has created for you.

Which one is appropriate for

the need that you have when you are designing a new visualization.

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