5a: Marks, Channels

Applied Perception

Marks

Marks are your basic graphical geometric elements.

E.g. points, bars, circles, lines, etc.

Channels

(aka Visual variables)

Channels encode information as attributes / properties of a mark.

E.g. Position, shape, size, color, etc.

Visualization:

Collection of marks (expressed via channels)

A visualization represents data using a collection of graphical marks such as bars, lines, and point symbols.

The attributes of a mark — such as its position, shape, size, or color — serve as channels in which we can encode underlying data values.

Channel: Identity vs Magnitude

This fruit chart encodes two data attributes as bar marks.

• It encodes number of people - a quantitative data set - as a vertical spatial magnitude channel.
• It encodes type of fruit - a nominal data set - as a horizontal spatial identity channel.
• Type of fruit is also encoded as a redundant color identity channel.

How many channels are there in this chart? What data scales are encoded?

How many channels are there in this chart? What data scales are encoded?

Channel: Expressiveness

The expressiveness principle dictates that the visual encoding should express all of, and only, the information in the dataset attributes.

Color channel violation of expressiveness principle:

Channel: Effectiveness

The effectiveness principle dictates that the importance of the attribute should match the salience of the channel; that is, its noticeability.

The most important attributes should be encoded with the most effective channels to be noticeable, and so on and so forth.

Channel effectiveness can be described by these principles:

• Accuracy
• Discriminability
• Separability
• Salience (pop-out)
• Grouping

Channel ranking (based on effectiveness)

Visualization Analysis and Design, chapter 5, Marks and Channels, Munzner

Human perception

Weber-Fechner Law

Weber: The minimum increase of stimulus which will produce a perceptible increase of sensation is proportional to the pre-existent stimulus.

Fechner: The intensity of our sensation increases as the logarithm of an increase in energy.

Weber-Fechner Law

Example of Weber's law using area

Weber-Fechner Law 2

Numberphile's video on Weber's Law

Steven's Power Law

Psychophysics: the subfield of psychology devoted to the systematic measurement of general human perception.

Graphical Perception: Cleveland and McGill

Reading: How William Cleveland Turned Data Visualization Into a Science

Reading: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods

Reading: Ranking Visualizations of Correlation Using Weber's Law

Channel effectiveness: Accuracy

Pick higher ranking channels (with reason).

E.g. Position > length > angles > area

Channel effectiveness: Discriminability

Must be able to discriminate between a reasonable number of bins (typically max 5 to 7)

So how to deal with lots of data? You use techniques like grouping, filtering or faceting (we'll cover in later lectures)

Channel effectiveness: Separability

Channels range from the seperable (e.g. position and hue) to the integral (e.g. multiple color scales)

Channel effectiveness: Salience (popout)

Storytelling with Data: A Data Visualization Guide for Business Professionals, chapter 4, Nussbaumer

Concept: Change blindness

A phenomenon of visual perception that occurs when a stimulus undergoes a change without this being noticed by its observer.

Change blindness demo

Change blindness in User Interfaces

So how to deal with this? Minimize changes, keep changes in the focal view, or use animations / transitions (we'll talk more about animations in later lectures)

Example: Elections SG

Questions?

Chi-Loong | V/R