Interaction

							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
      The 3 Feedback Loops
• Visual-Manual Control
• View Refinement and Navigation
• Problem Solving
     Visual-Manual Control Loop
    Data manipulation loop, through which objects are
    selected and moved using the basic skill of eye-hand
    coordination.

•   Low level interaction
•   Visual control of hand position
•   Selection of objects on the screen
•   Reaction times
   Choice Reaction Times

• How fast can you choose something?
• Visual signal: 130 msec response time
• 700 msec if signals aren’t expected
    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)
    Visual-Manual Feedback Loop

       Detect start         Judge distance    Human processing
         signal                to target
                      no                     Effect hand
               In target?                    movement
       yes

Next task
                        Machine processing
            Update display        Measure hand position
            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
                  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
    View Refinement & Navigation
               Loop
•   Exploration of extended, detailed spaces
•   Locomotion
•   Viewpoint control
•   Map orientation
•   Focus, context, scale
•   Rapid interaction with data
       Navigation Control Loop

  Spatial                                       Cognitive
                                Working
data model                                     logical and
                                memory
                                              spatial model

         Visualization            Assess
            of task              progress

 Computer
 databases         Navigation
                    control            Long-term memory
              Locomotion

• Moving gives dimensionality to space
• Movement should correspond to real life
• Relative movement over time is more
  important than smooth motion
     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
             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”
           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
                Walking
• Walk around in virtual reality
• Movement in real world constrained (using
  treadmills)
• Good: relevant to typical locomotion
• Bad:?
                    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)
            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
            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
            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?
       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
        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
                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
  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
    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)
       Problem-Solving Loop
• Using visual representations of data to solve
  problems
• Interactive cycle, use a conceptualization as
  aid to finding solution
          Problem-Solving Loop

 Computer                        Visual-spatial
                Refine and test                     Working
based model                         model
              hypotheses through                    memory
                 visualization

         Visualization          Cognitive logical
            of task              verbal model

 Computer
 databases         Navigation
                    control            Long-term memory
                                            network
           Human Memory
•    3 Types
1.   Iconic
2.   Working
3.   Long-term
            Iconic Memory
• Simple visual buffer holds retinal images
• Will quickly deteriorate if not read out
• The interface between computer display and
  human processing system
            Working Memory
•   Limited in capacity
•   A ‘cache’ of sorts for human processor
•   Separate subsystems for different tasks
•   A general purpose working memory?
         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
         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
  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
        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
              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