Marks and Channels, Data Types CS 7250 S PRING 2020 Prof. Cody - - PowerPoint PPT Presentation

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Marks and Channels, Data Types CS 7250 S PRING 2020 Prof. Cody - - PowerPoint PPT Presentation

Dec 11, 2023 270 likes •803 views

Marks and Channels, Data Types CS 7250 S PRING 2020 Prof. Cody Dunne N ORTHEASTERN U NIVERSITY Slides and inspiration from Michelle Borkin, Krzysztof Gajos, Hanspeter Pfister, 1 Miriah Meyer, Jonathan Schwabish, and David Sprague I N -C LASS P

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Marks and Channels, Data Types

CS 7250 SPRING 2020

  • Prof. Cody Dunne

NORTHEASTERN UNIVERSITY

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Slides and inspiration from Michelle Borkin, Krzysztof Gajos, Hanspeter Pfister, Miriah Meyer, Jonathan Schwabish, and David Sprague

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IN-CLASS PROGRAMMING — SOUTH END ALTAIR

~25 min total

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PREVIOUSLY, ON CS 7250…

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“Graphical Integrity”

To achieve graphical “excellence” according to Tufte:

  • 1. Above all else show the data.
  • 2. Maximize the data-ink ratio.
  • 3. Erase non-data ink.
  • 4. Erase redundant data ink.
  • 5. Revise and edit.

Tufte, “Visual Display of Quantitative Information” (1983)

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“Chart Junk”

Take-away: it depends on your audience, task, and context... Chart junk can... persuade, help with memorability, engage Chart junk can... bias, limit data-ink ratio, clutter, lower trust

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NOW, ON CS 7250…

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MARKS AND CHANNELS

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GOALS FOR TODAY

  • Learn the basic visual primitives of visualizations

(marks and channels)

  • Understand how marks and channels are

assembled to make visualizations

  • Learn which marks and channels are most

effective for a given task (“perceptual ordering”)

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MARK = basic graphical element in an image

Visualization Building Blocks

Munzner, “Visualization Analysis and Design” (2014)

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CHANNEL = way to control the appearance of marks, independent of the dimensionality of the geometric primitive

Visualization Building Blocks

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 2

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 2

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 3

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 4

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 2

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 2

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CHANNEL :

Visualization Building Blocks

MARK:

# of attributes encoded: 3

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CHANNEL :

Visualization Building Blocks

MARK:

+ position in 3D space # of attributes encoded: ?

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Kindlmann (2004)

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Kindlmann (2004)

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Visualization Building Blocks

Munzner, “Visualization Analysis and Design” (2014)

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Visualization Building Blocks

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Visualization Building Blocks

Channels :

Note: these are all really important concepts when it comes time to coding your visualizations...!

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How do I pick which marks or channels to use?

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“Ordering of Elemental Perceptual Tasks”

Cleveland & McGill (1984)

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“Ordering of Elemental Perceptual Tasks”

Cleveland & McGill (1984)

TASK: Which segment/bar is the maximum, and what is its percentage/value?

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“Ordering of Elemental Perceptual Tasks”

Cleveland & McGill (1984)

This is why pie charts are bad for quantitative tasks

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https://www.washingtonpost.com/news/wonk/wp/2013/06/17/the-usefulness-of-pie-charts-in-two-pie-charts/

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http://www.datasciencecentral.com/profiles/blogs/10-resources-to-help-you-stop-doing-pie-charts

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William Playfair (1801)

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“Ordering of Elemental Perceptual Tasks”

Cleveland & McGill (1984)

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“Ordering of Elemental Perceptual Tasks”

Heer & Bostock (2010)

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Heer & Bostock (2010)

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Expressiveness and Effectiveness

Expressiveness principle: the visual encoding should express all

  • f, and only, the information in the

dataset attributes. (i.e., data characteristics should match the channel)

Mackinlay (1986)

Effectiveness principle: the importance of the attribute should match the salience of the channel; that is, its noticeability. (i.e., encode most important attributes with highest ranked channels)

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My Summary: Prioritize choosing the most appropriate channel for each attribute

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Expressiveness and Effectiveness

Mackinlay (1986)

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Expressiveness and Effectiveness

Mackinlay (1986)

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Expressiveness and Effectiveness

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IN-CLASS EXERCISE

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3, 12, 42

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3, 12, 42

Jonathan Schwabish In-class Sketching: “Three numbers”

20m 1. Break-out into groups of ~3 students. 2. Together (15m) use pens & post-it notes to sketch as many possible visualizations as you can of these three numbers. 3. No upload required 4. As a class (5m) we will discuss some of the designs and themes.

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DATA TYPES

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GOALS FOR TODAY

  • Learn what are data types and dataset types
  • Learn what are attribute types
  • Learn how to pick appropriate visual representations

based on attribute type and perceptual properties

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TYPE = structural or mathematical interpretation of the data

Data Types

(variable, data dimension) (row, node) (relationship) (spatial location) (sampling)

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DATASET = collection of information that is the target of analysis

Data Types

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Data Types

DATASET = collection of information that is the target of analysis

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Slides by Miriah Meyer

Relevant to anyone in the sciences!

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Slides by Miriah Meyer

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https://en.wikipedia.org/wiki/Voronoi_diagram

“Voronoi Tessellation”