What We Are Going to L earn

• Faceting
  • Juxtapose
  • Partition
  • Superimpose
• Shared data
• Shared encoding
• Shared navigation
• Dashboarding in a box
• Architecture for visualization

Facet Across Multiple Views

Facet

Juxtapose

Juxtapose

• Design choices
  • View count
    • Few vs. many
  • View visibility
  • View arrangment
    • User-managed vs. system-aligned
• Why juxtapose views?
  • Benefits: eyes vs. memory
    • Lower cognitive load to move eyes between two views than remembering previous state with single changing view
  • Costs: display area, two views side-by-side each have only half the area of one view

Share Encoding

Idiom: Overivew-Detail Views

System: Google Maps

• Encoding: same
• Data: subset shared
• Navigation: shared
  • Bi-directional linking
• Differences:
  • Viewpoint
  • (Size)
• Special case: bird's-eye map

Idiom: Small Multiples

System: cerebral

• Encoding: same
• Data: none shared
• Different attributes for node colors
• (Same network layout)
• Navigation: shared

Focus/Context

Same encoding/subset of data/linked navigation

Small Multiples (Cubism)

Same encoding/different data/linked navigation

Share Data

Idiom: Linked Highlighting

System: EDV

• See how regions contiguous in one view are distributed within another
• Powerful and pervasive interaction idiom
• Encoding: different
• Multiform
• Data: all shared
• AKA: brushing and linking

Linked Filtering (Crossfilter)

Multiform Overview (Treeversity)

Different encoding/all data/linked navigation

System: Improvise

• Investigate power of multiple views
• Pushing limits on view count, interaction complexity
• How many is okay?
• Open research question
• Reorderable lists
• Easy lookup
• Useful when linked to other encodings

Improvise

Share Navigation

Partition

Partition Into Views

• How to divide data between views
  • Split into regions by attributes
  • Encodes association between items using spatial proximity
  • Order of splits has major implications for what patterns are visible
• No strict dividing line
  • View: big/detailed
    • Contiguous region in which visually encoded data is shown on the display
  • Glyph: small/iconic
    • Object with internal structure that arises from multiple marks

Partitioning: Recursive Subdivision, Part I

System: HIVE

• Split by neighborhood
• Then by type
• Then time
  • Years as rows
  • Months as columns
• Color by price


• Neighborhood patterns
  • Where it’s expensive
  • Where you pay much more for detached type

Partitioning: Recursive Subdivision, Part II

System: HIVE

• Switch order of splits
  • Type then neighborhood
• Switch color
  • By price variation
• Type patterns
  • Within specific type, which neighborhoods inconsistent

Partitioning: Recursive Subdivision, Part III

System: HIVE

• Different encoding for second-level regions
• Choropleth maps

Partitioning: Recursive Subdivision, Part IV

System: HIVE

• Size regions by sale counts
• Not uniformly
• Result: treemap

Superimpose

Superimpose Layers

• Layer: set of objects spread out over region
• Each set is a visually distinguishable group
• Extent: whole view
• Design choices
• How many layers, how to distinguish?
• Encode with different, nonoverlapping channels
• Two layers achieveable, three with careful design
• Small static set, or dynamic from many possible?

Static Visual Layering

• Foreground layer: roads
• Hue, size distinguishing main from minor
• High luminance contrast from background
• Background layer: regions
• Desaturated colors for water, parks, land areas
• User can selectively focus attention
• “Get it right in black and white”
• Check luminance contrast with greyscale view

Suprimposing Limits

• Few layers, but many lines
• Up to a few dozen
• But not hundreds
• Superimpose vs. juxtapose: empirical study
• Superimposed for local, multiple for global
• Tasks
• Local: maximum, global: slope, discrimination
• Same screen space for all multiples vs single superimposed

Dynamic Layering

Applying the
Visualization Mantra

Similian

LifeFlow

LifeFlow How-To

LifeFlow Demo

TreeVersity

What we Learned

• Faceting
  • Juxtapose
  • Partition
  • Superimpose
• Shared data
• Shared encoding
• Shared navigation
• Dashboarding in a box
• Architecture for visualization