Space/Order

1
Space/Order
CS-533C Reading Presentation

• Quanzhen Geng
• (Master of Software Systems Program)
• January 27, 2003

2
Space/Order Encodings

• Definition
• Space/order encodings transform data in
  information space into a spatial representation
  (size and order) in display space that preserves
  informational characteristics of the dataset and
  facilitates our visual perception and
  understanding of the data.
• Importance
• Finding a good spatial representation of the
  information at hand is one of the most difficult
  and also the most important tasks in information
  visualization.

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Two challenges ofSpatial Encodings

• (1) Visualizing large information space
• (Large Maps, Tables, Documents etc.)
• through a relatively small window screen.
• Lack of screen space
• (2) Visualizing multi-dimensional data (ngt3) in
  2D space
• How to effectively present more than 3
  dimensions of
• information in a visual display with 2 (to 3)
  dimensions?

How to display 1,000,000 rows of table on
screen?
What does 10-D space look like?
4
Solving the Problems inSpatial Encodings

• Two important spatial representation
  techniques
• Spatial distortions
• solve the lack of screen space problem
• Parallel coordinates
• Non-projective mapping between N-D and 2-D

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Distortions

• Problems
• Large Computer-Based Information Systems
• Small Window as Single Access-Point
• Difficult to Interpret Single Information
  Items
• when Viewing it Outside of its Context
• Definition
• Distortion is a visual transformation that
  modifies a Visual Structure to create
  focuscontext views.
• Want to achieve
• Focus to see detail of immediate interest
• Context to see the overall picture
• Want to solve
• The problem of displaying a large information
  space through a relatively small window, i.e.,
  lack of screen space problem.

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Principles of distortions
Transformation function Magnification function
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Distortions

• Methods of distortions (focuscontext views)
• --Bifocal Display
• --Perspective wall
• --Document lens
• --Fisheye views
• --Table lens
• Major differences of these methods
• --Transformation function
• --Magnification function

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Bifocal Display

• First suggested by Spence and Apperley (1980?).
• Combination of a detailed view and two distorted
  sideview.
• One-dimensional form.

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Bifocal Display
Fold
Project
www.ifs.tuwien.ac.at/silvia/wien/vu-infovis/PDF-F
iles/InfoVis-6.pdf
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What is the Bifocal Display Doing?

• Transform the information space to the display
  space with
• Visual transformation functions

www.comp.leeds.ac.uk/kwb/VIS/v02_16.ppt
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Early implementation of Bifocal Display (1980)
www.ifs.tuwien.ac.at/silvia/wien/vu-infovis/PDF-F
iles/InfoVis-6.pdf
12
Perspective Wall

• A technique for viewing and navigating large,
  linearly-structured information (for instance,
  chronological / alphabetical data), allowing the
  viewer to focus on a particular area while still
  maintaining some degree of location or context.
• Extension or descendant of Bifocal Display.
• 3D aspect decreases cognitive load.

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Perspective Wall vs. Bifocal Display
Bifocal Display
Perspective Wall
2D view
3D view

• Perspective Wall
• 3D view
• Center panel to view detail
• Perspective panels to view context

www.sims.berkeley.edu/courses/is247/s02/lectures/Z
oomingFocusContextDistortion.ppt
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Perspective Wall
Mackinlay et al.c 1991
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Perspective Wall

• In terms of transformation function, the
  situation is closer to the bifocal display.
• Perspective gives smoother transition from focus
  to context.

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Perspective WallExample 1 project schedule
Map work charts onto diagram. x-axis is time,
y-axis is project. (Mackinlay, Robertson, Card
91)
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Perspective WallExample 2 file navigation

• Typical example use is file navigation
• Shown by date, type
• However few files can be displayed at once

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Perspective WallExample 3 file navigation
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Features of Perspective Wall

• Folding is used to distort a 2-D layout into a
  3-D visualization,using hardware support for 3-D
  interactive animation.
• Perspective panels are shaded to enhance the
  effect of 3-D.
• Vertical dimension can be used to visualize
  layering information.
• Disadvantage
• Wastes the corner areas of the screen.

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Document Lens
Why -Text too small to read but yet needed to
perceive patterns.
-Perspective wall wastes corner areas of
screen What General visualization technique
based on a common strategy for
understanding paper documents when
their structure is not
known. How 3D Visualization Tool For Large
Rectangular Presentations
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Document Lens Features

• Lens rectangular interested in text that is
  mostly rectangular
• Sides are elastic and pull the surrounding parts
  towards the lens creating a pyramid

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Document Lens
Document lens, 3-D effect, no waste of corner
space
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Comparison with other approaches
Bifocal Display
Perspective Wall
Document Lens
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Fisheye View (Distortion)

• When people think about focuscontext views, they
  typically think of the Fisheye View (Distortion)
• First introduced by George Furnas in his 1981
  report
• Provides detailed views (focus) and overviews
  (context) without obscuring anythingThe focus
  area (or areas) is magnified to show detail,
  while preserving the context, all in a single
  display.
• 
  -(Shneiderman, DTUI, 1998)

www.cc.gatech.edu/classes/AY2002/cs7450_spring/
Talks/10-focuscontext.ppt
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Principles of Fisheye View

• Continuous Magnification Functions
• Can distort boundaries because applied radially
  rather than x y

http//davis.wpi.edu/matt/courses/distortion/fis
heye
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Fisheye-view vs. Bifocal display
Bifocal Display
Fisheye-view
http//davis.wpi.edu/matt/courses/distortion/fis
heye
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Fisheye View Application 1 Map of Washington
D.C.
web.mit.edu/16.399/www/course_notes/context_and_de
tail1.pdf
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Fisheye ViewApplication 2 viewing network nodes
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Fisheye View Application 3 fisheye menu
Dynamically change the size of a menu item to
provide a focus area around the mouse pointer,
while allowing all menu items to remain on screen

• All elements are visible but items near cursor
  are full-size, further away are smaller
• bubble of readable items move with cursor

www.comp.leeds.ac.uk/kwb/VIS/v02_16.ppt
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Fisheye View Application 4 fisheye table
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Table Lens
The Table Lens Merges Graphical and Symbolic
Representations in an Interactive Focus Context
Visualization for Tabular Information.
(Ramana Rao and
Stuart K. Card)
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Table Lens Features

• Focus context for large datasets while
  retaining access to all data
• Works best for case / variable data flexible,
  suitable for many domains
• Cell contents coded by color (nominal) or bar
  length (interval)
• Tools zoom, adjust, slide
• Search / browse (spotlighting)
• Create groups by dragging columns

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Table Lens

• Distortion in each dim. is independent
• Multiple focal areas
• Degree of Interest (DOI)
• Interactive Focus Manipulation

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DOI (Degree of Interest)

• Maps from an item to a value that indicates the
  level of interest in the item.

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Table Lens Focus Manipulation
Zoom, adjust and slide provides interactive
focus manipulation
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Table Lens
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Parallel Coordinates

• Issues
• How to effectively present more than 3 dimensions
  of information in a visual display with 2 (to 3)
  dimensions?
• How to effectively visualize very large, often
  complex data sets?

www.sims.berkeley.edu/courses/is247/s02/lectures/M
ultidimensionalDataAnalysis.ppt
38
Parallel Coordinates -Goals

• We want to
• Visualize multi-dimensional data
• Without loss of information
• With
• Minimal complexity
• Any number of dimensions
• Variables treated uniformly
• Objects remain recognizable across
  transformations
• Easy / intuitive conveyance of information
• Mathematically / algorithmically rigorous
• (Adapted from Inselberg)

www.sims.berkeley.edu/courses/is247/s02/lectures/M
ultidimensionalDataAnalysis.ppt
39
Parallel CoordinatesVisualizing N variables on
one chart

• Create N equidistant vertical axes, each
  corresponding
• to a variable
• Each axis scaled to min, max range of the
  variable
• Each observation corresponds to a line drawn
  through
• point on each axis corresponding to value of
  the variable

www.comp.leeds.ac.uk/kwb/VIS/v02_14.ppt
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Parallel Coordinates

• -- Correlations may start to appear as the
  observations are plotted on the chart
• -- Here there appears to be negative correlation
• between values of A and B for example
• -- This has been used for applications with
• thousands of data items

www.comp.leeds.ac.uk/kwb/VIS/v02_14.ppt
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Cartesian vs. Parallel Coordinates
infovis.cs.vt.edu/cs5984/students/parcoord.ppt
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Parallel Coordinates Example 1 Correlations
Detroit homicide data 7 variables 13 observations
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Parallel Coordinates -Example 2 Air traffic
control
Cartesian Coordinates
Parallel Coordinates
http//www.caip.rutgers.edu/peskin/epriRpt/Parall
elCoords.html
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Parallel Coordinates Advantages

• Multi-dimensional data can be visualized in
• two dimensions with low complexity.
• Each variable is treated uniformly.
• Relations within multi-dimensional data can
• be discovered (data mining).
• Because of its visual cues, can serve as a
• preprocessor to other methods.

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Parallel Coordinates Disadvantages

• Close axes as dimensions increase.
• Clutter can reduce information perceived.
• Varying axes scale, although indicating
• relationships, may cause confusion.
• Connecting the data points can be misleading.

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Disadvantage Level of Clutter Taken from
Hierarchical Parallel Coordinates Ying-Huey
Fua, Elke A. Rundensteiner, Matthew O. Ward
16,384 records in 5 dimensions causes
over-plotting.
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Improvement SummarizationTaken from
Hierarchical Parallel CoordinatesYing-Huey
Fua, Elke A. Rundensteiner, Matthew O. Ward. 
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Improvement Level-Of-Detail (LOD)Taken from
Hierarchical Parallel CoordinatesYing-Huey
Fua, Elke A. Rundensteiner, Matthew O. Ward. 
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Improvement BrushingTaken from Hierarchical
Parallel CoordinatesYing-Huey Fua, Elke A.
Rundensteiner, Matthew O. Ward. 
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Summary

• Spatial encoding the most important encoding
• The good and bad of spatial distortion
• The advantages and disadvantages of parallel
  coordinates