36
Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Embed Size (px)

Citation preview

Page 1: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Interacting with Visualization

Colin Ware, Information Visualization, Chapter 10, page 335

Page 2: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Introduction

• Visualization give us interfaces for complex computer-based systems

• Interaction reduces cognitive load

• 3 classes of interlocking feedback loops

Page 3: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

The 3 Feedback Loops

• Visual-Manual Control

• View Refinement and Navigation

• Problem Solving

Page 4: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Visual-Manual Control Loop

• Low level interaction

• Visual control of hand position

• Selection of objects on the screen

• Reaction times

Data manipulation loop, through which objects are selected and moved using the basic skill of eye-hand coordination.

Page 5: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Choice Reaction Times

• How fast can you choose something?

• Visual signal: 130 msec response time

• 700 msec if signals aren’t expected

Page 6: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

2D Positioning and Selection

• How fast can you select something (from a display, including positioning)?

• Selection using a mouse is one of the most common interactive operations in the modern graphical user interface.

• Selection time = a + b log2 (D / W + 1.0) Where D is the distance to the centre of the target, W is the width of the target, and a and b are constants determined empirically.

(Fitts’ law)

Page 7: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Visual-Manual Feedback Loop

Detect startsignal

Judge distanceto target

Effect handmovementIn target?

Update display Measure hand position

no

yes

Next task

Human processing

Machine processing

Page 8: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Skill Learning

• Applies to repeated tasks over time

• Experience is a large factor in learning

• Design interfaces should minimize learning new tasks

• People can tolerate small changes

Page 9: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Vigilance

• Principle: target detection

• Is this boring? Vigilance is hard

1. Vigilance drops greatly over first hour

2. Fatigue large negative influence

3. Need to focus, no multitasking

4. Irrelevant signals reduce vigilance

Page 10: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

View Refinement & Navigation Loop

• Exploration of extended, detailed spaces

• Locomotion

• Viewpoint control

• Map orientation

• Focus, context, scale

• Rapid interaction with data

Page 11: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Navigation Control Loop

Spatialdata model

Computerdatabases

Visualizationof task

Long-term memory

Cognitivelogical and

spatial model

Workingmemory

Assessprogress

Navigationcontrol

Page 12: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Locomotion

• Moving gives dimensionality to space

• Movement should correspond to real life

• Relative movement over time is more important than smooth motion

Page 13: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Spatial Navigation Metaphors

• Movement is usually constrained to avoid confusion (affordances)

• 4 main classes of movement metaphors:

1. World-in-hand

2. Eyeball-in-hand

3. Walking

4. Flying

Page 14: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

World-in-hand

• Perception that the environment is moving, observer is stationary

• Good: for discrete, relatively compact data objects

• Bad: for long distances, extended terrains

• Used in: computer game “Black & White”

Page 15: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335
Page 16: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Eyeball-in-hand

• Camera (or eye) is manipulable

• Not the most effective method for viewpoint control

• Good: ?

• Bad: occlusion, hard to get some views, limited by user’s hand positions

Page 17: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Walking

• Walk around in virtual reality

• Movement in real world constrained (using treadmills)

• Good: relevant to typical locomotion

• Bad:?

Page 18: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Flying

• Navigation as if in an airplane

• Unconstrained movement

• More flexible, usable than other interfaces

• Good: relevant to typical locomotion

• Bad: given real flight controls, users were confused (users had to learn a new skill)

Page 19: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Reading Maps

• How to get from here to there (Siegel)

1. Declare key landmarks

2. Develop rules for connecting key landmarks, things in between

3. Form cognitive spatial map for distances between landmarks and relative position

Page 20: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Landmark rules

• In virtual environments,

1. Should be enough landmarks visible at all times

2. Landmarks should be visually distinct

3. Landmarks should be seen at every scale

4. Landmarks should be placed in areas of interest

Page 21: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Map Orientation

• Track-up display orientation– Up is always the correct way to go– ‘Right’ is always ‘right’

• North-up display orientation– North is up, use a compass– ‘Right’ becomes ‘left’ if you go ‘down’– Common frame of reference?

Page 22: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Visualizing with Maps

• Overview maps are important if the space is large

• User location and direction should be noted

• Key landmark images should be provided

• Instructions other than the map should be provided for navigation

Page 23: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Focus, Context, Scale

• Spatial Scale: understanding how changes in scale relate

• Structural Scale: levels of detail give us an appropriate amount of information

• Temporal Scale: time compression and data samples from many different time ranges

Page 24: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Distortion

• Hide information that the user doesn’t need to see by focusing attention where it’s relevant

• Fish eye, table lens, hyperbolic tree browser are good examples of distortion

Page 25: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Other Navigation Techniques

• Rapid zooming

• Elision techniques– Hiding information until it is needed, give

appearance of data being far away, unimportant

• Multiple Windows– One context each, but each window is linked

Page 26: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Rapid Interaction with Data

• Interaction should be fluid and dynamic

• Users have to relate cause and effect

• Users may want to customize how visualization system displays their data– Brushing: highlighting individual data elements

interactively (parallel coordinates)

Page 27: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Problem-Solving Loop

• Using visual representations of data to solve problems

• Interactive cycle, use a conceptualization as aid to finding solution

Page 28: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Problem-Solving Loop

Computerbased model

Computerdatabases

Visualizationof task

Long-term memorynetwork

Visual-spatialmodel Working

memory

Cognitive logicalverbal model

Navigationcontrol

Refine and testhypotheses through

visualization

Page 29: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Human Memory

• 3 Types

1. Iconic

2. Working

3. Long-term

Page 30: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Iconic Memory

• Simple visual buffer holds retinal images

• Will quickly deteriorate if not read out

• The interface between computer display and human processing system

Page 31: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Working Memory

• Limited in capacity

• A ‘cache’ of sorts for human processor

• Separate subsystems for different tasks

• A general purpose working memory?

Page 32: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Long-term Memory

• Lifelong memory

• Includes: episodic memory, motor skills, perceptual skills

• Estimated: 109 bits (~100 megabytes) stored over 35 year period

• Ideas, thoughts get lost in concept network

• Misremembering events over time

Page 33: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Chunks & Concepts

• A chunk is a piece of information as a mental representation

• Chunks are either specific or general; high-level concepts are a result of experience

• Concepts formed from hypothesis testing process, starting from an initial idea

Page 34: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Human Computer Similarities

• Both systems share common traits:– Registers / Iconic Memory– Caches / Working Memory– Main Memory or storage / Long-term memory

• How is this possible?– Known to be efficient using computers

Page 35: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Not Really the Same

• Digital information is much more detailed

• Digital information can be retained indefinitely

• Human visual memory tends to dissipate

• Human storage isn’t thought of as atomic elements but of chunks and concepts

Page 36: Interacting with Visualization Colin Ware, Information Visualization, Chapter 10, page 335

Conclusion

• Similar structures exist in humans to interact, navigate and problem solve

• Feedback loops are common structures that reinforce positive behavior

• Visualization aids problem solving