Interaction Maneesh Agrawala CS 448B: Visualization Fall 2018 1 - - PDF document

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Interaction Maneesh Agrawala CS 448B: Visualization Fall 2018 1 - - PDF document

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Interaction Maneesh Agrawala CS 448B: Visualization Fall 2018 1 Last Time: Perception Just noticeable difference JND (Weber s Law) Ratios more important than magnitude Most continuous variations in stimuli are perceived in

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Interaction

Maneesh Agrawala

CS 448B: Visualization Fall 2018

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Last Time: Perception Just noticeable difference

JND (Webers Law)

■

Ratios more important than magnitude

■

Most continuous variations in stimuli are perceived in discrete steps

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Stevens power law

p < 1 : underestimate p > 1 : overestimate [graph from Wilkinson 99, based on Stevens 61] [Cleveland and McGill 84]

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[Cleveland and McGill 84]

Relative magnitude estimation

Most accurate Position (common) scale Position (non-aligned) scale Length Slope Angle Area Volume Least accurate Color hue-saturation-density

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Gestalt

Principles

■ figure/ground ■ proximity ■ similarity ■ symmetry ■ connectedness ■ continuity ■ closure ■ common fate ■ transparency

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Figure/Ground

http://www.aber.ac.uk/media/Modules/MC10220/visper06.html

Ambiguous Principle of surroundedness Principle of relative size

Figure/Ground

Ambiguous Unambiguous

http://www.aber.ac.uk/media/Modules/MC10220/visper06.html

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Proximity

[Ware 00]

Similarity

Rows dominate due to similarity [from Ware 04]

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Symmetry

Bilateral symmetry gives strong sense of figure [from Ware 04]

Connectedness

Connectedness overrules proximity, size, color shape [from Ware 04]

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Continuity

We prefer smooth not abrupt changes [from Ware 04] Connections are clearer with smooth contours [from Ware 04]

Continuity: Vector fields

Prefer field that shows smooth continuous contours [from Ware 04]

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Closure

We see a circle behind a rectangle, not a broken circle [from Ware 04] Illusory contours [from Durand 02]

Common fate

http://coe.sdsu.edu/eet/articles/visualperc1/start.htm

Dots moving together are grouped

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Transparency

Requires continuity and proper color correspondence [from Ware 04]

Layering and Small Multiples

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Layering: Gridlines

Electrocardiogram tracelines [from Tufte 90]

Layering: Gridlines

Stravinsky score [from Tufte 90]

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Setting Gridline Contrast

How light can gridlines be and remain visible? How dark can gridlines be and not distract? Safe setting: 20% Alpha

[Stone & Bartram 2009]

Layering: Color and line width

IBM Series III Copier [from Tufte 90]

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Small multiples

[Figure 2.11, p. 38, MacEachren 95]

Small multiples

Operating trains. Redrawn by Tufte to emphasize colored lights. [fromTufte 90]

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Change blindness

[Example from Palmer 99, originally due to Rock]

Change detection

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Change detection Rensinks demonstration

http://www.csc.ncsu.edu/faculty/healey/PP/index.html

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Summary

Choosing effective visual encodings requires knowledge of visual perception Visual features/attributes

■ Individual attributes often preattentive ■ Multiple attributes may be separable, often

integral

Gestalt principles provide higher level design guidelines We dont always see everything that is there

Announcements

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A2: Exploratory Data Analysis

Use Tableau to formulate & answer questions First steps

■ Step 1: Pick a domain ■ Step 2: Pose questions ■ Step 3: Find data ■ Iterate

Create visualizations

■ Interact with data ■ Question will evolve ■ Tableau

Make wiki notebook

■ Keep record of all steps

you took to answer the questions

Due before class on Oct 15, 2018

Interaction

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Gulfs of execution & evaluation

Real world Conceptual model

Evaluation Execution

Gulfs

[Norman 1986]

Gulf of Execution

The difference between the users intentions and the allowable actions.

Gulf of Evaluation

The amount of effort that the person must exert to interpret the state of the system and to determine how well the expectations and intentions have been met.

[Norman 1986]

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Gulf of evaluation

Real world: Conceptual model: x,y correlated?

Evaluation Gulf

X Y 0.67 0.79 0.32 0.63 0.39 0.72 0.27 0.85 0.71 0.43 0.63 0.09 0.03 0.03 0.20 0.54 0.51 0.38 0.11 0.33 0.46 0.46

Gulf of evaluation

Real world: Conceptual model: x,y correlated?

Evaluation Gulf

0.5 1 0.5 1 X Y

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Gulf of evaluation

Real world: Conceptual model: x,y correlated?

Evaluation

Gulf

r = -.29

Gulf of execution

Real world

Conceptual model: Draw a scatterplot

Execution

Gulf

Move 90 30 Rotate 35 Pen down …

0.5 1 0.5 1 X Y

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Gulf of execution

Gulf Execution

Conceptual model: Draw a scatterplot

0.5 1 0.5 1 X Y

Real world

Topics

Early interactive systems Brushing and linking Dynamic queries Generalized selections

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Early Systems

[Graphics and Graphic Information Processing, Bertin 81]

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Bertin Matrices

Research question Table

  • 1. Encode table cells visually
  • 2. Group similar rows and columns

to reveal patterns

[Graphics and Graphic Information Processing, Bertin 81]

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Group similar rows and columns

Choose a row with a particular visual

  • aspect. Move to extremity of matrix

Move similar rows close, opposite rows to

  • bottom. (Creates two opposing groups

and a middle group) Repeat for columns (??) Iterate

[Graphics and Graphic Information Processing, Bertin 81]

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[Graphics and Graphic Information Processing, Bertin 81] [Graphics and Graphic Information Processing, Bertin 81]

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[Graphics and Graphic Information Processing, Bertin 81]

Bertifier [Perin 2014]

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Bertifier [Perin 2014]

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Pointing

Basic Pointing Methods

Point Selection Mouse Hover / Click Touch / Tap Select Nearby Element (e.g., Bubble Cursor)

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Basic Pointing Methods

Point Selection Mouse Hover / Click Touch / Tap Select Nearby Element (e.g., Bubble Cursor) Region Selection Rubber-band or Lasso Area Cursors (“Brushes”)

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Brushing and Linking

Focus user attention on a subset of the data within one graph [from Wills 95]

Highlighting

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Brushing

■ Interactively select subset of data ■ See selected data in other views ■ Two things (normally views) must be

linked to allow for brushing

Brushing Scatterplots

Brushing Scatterplots, Becker & Cleveland 1982

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Baseball statistics [from Wills 95]

select high salaries avg career HRs vs avg career hits (batting ability) avg assists vs avg putouts (fielding ability) how long in majors distribution

  • f positions

played

Linking assists to positions

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GGobi: Brushing

http://www.ggobi.org/

Dynamic Queries

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Query and results

SELECT house FROM east bay WHERE price < 1,000,000 AND bedrooms > 2 ORDER BY price

Issues

  • 1. For programmers
  • 2. Rigid syntax
  • 3. Only shows exact matches
  • 4. Too few or too many hits
  • 5. No hint on how to reformulate the query
  • 6. Slow question-answer loop
  • 7. Results returned as table
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[Ahlberg and Schneiderman 92]

HomeFinder Direct manipulation

  • 1. Visual representation of objects and actions
  • 2. Rapid, incremental and reversible actions
  • 3. Selection by pointing (not typing)
  • 4. Immediate and continuous display of

results