Transcript Overview of Information Visualization II

ICS 280: Advanced Topics in Information Visualization
Professor Alfred Kobsa
Overview of Information Visualization II
April 12, 2001
Víctor González ([email protected])
ICS 280: Information Visualization
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Definitions (1)
• External Cognition
Use of external world to accomplish cognition.
Cognitive artifacts e.g. Post-it notes, bookmarks, wedding ring.
• Information design
Design of external representations to amplify cognition.
e.g. Maps.
• Data graphics
Use of abstract, nonrepresentational visual representations of data to
amplify cognition.
Víctor González ([email protected])
ICS 280: Information Visualization
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Definitions (2)
• Visualization
Use of computer-based, interactive visual representations of data to
amplify cognition
• Scientific visualization
Use of interactive visual representations of scientific data, typically
physically based, to amplify cognition.
• Information visualization
Use of interactive visual representation of abstract, nonphysically
based data to amplify cognition.
e.g. Business information.
* large amount of data
* interactivity
Víctor González ([email protected])
ICS 280: Information Visualization
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How Visualization Amplifies Cognition (1)
Classic study of Larkin and Simon (1987)
Solving physics problems using diagrams vs using non-diagrammatic
representations. They compared the effort to do search, recognition,
and inference.
(1) By grouping together information that is used together large
amounts of search were avoided.
(2) By using location to group information about a single element, the
need to match symbolic labels was avoided, leading to reductions
in search and working memory.
(3) The visual representation automatically supported a large number of
perceptual inferences that were extremely easy for humans.
e.g. Recognize geometric elements like alternate interior angles
Víctor González ([email protected])
ICS 280: Information Visualization
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How Visualization Amplifies Cognition (2)
(1) Increased Resources
- Expanded working memory available for solving a problem °
- Expanded storage of information - quickly accessible massive amounts
of information.
(2) Reduced Search
- Visualizations group information used together, reducing search.
- Representation of large amount of data in a small space.
(3) Enhanced Recognition of Patterns
- Recognition instead of recall (menu based vs command interface)
- Visually organizing data by structural relationships enhances patterns
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ICS 280: Information Visualization
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How Visualization Amplifies Cognition (3)
(4) Perceptual Inference
- Visual representations make some problems obvious e.g. geometry of
a problem helps to find solutions.
- Visualization can enable complex specialized graphical computations.
(5) Perceptual Monitoring
- Visualization can allow the monitoring of a large number of
potential events if the display is organized so that these stand out by
appearance or motion.
(6) Manipulable medium
- Unlike static diagrams, visualizations can allow exploration of a space
of parameter values and can amplify user operations.
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ICS 280: Information Visualization
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How Visualization Amplifies Cognition (4)
• LifeLines
http://www.cs.umd.edu/hcil/lifelines/
Lifelines provides a general visualization environment for medical
records. It eliminates long lists to scroll, complex searches, endless
menus, etc. A one screen overview of the record using timelines
provides direct access to the data.
For a patient record, medical problems, hospitalization and
medications can be represented as horizontal lines, while icons
represent discrete events such as physician consultations,
progress notes or tests. Line color and thickness can illustrate
relationships or significance. Rescaling tools and filters allow users to
focus on part of the information, revealing more details.
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ICS 280: Information Visualization
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How Visualization Amplifies Cognition (5)
• Inxight Tree Studio
http://www.inxight.com/index.html
Inxight Tree Studio allows web site builders to create visual
site maps called Star Trees.
The users can see at a glance all the organization of the web site.
Search features that improve the navigation
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ICS 280: Information Visualization
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How Visualization Amplifies Cognition (6)
• On-line Library of Information Visualization Environments
http://www.otal.umd.edu/Olive/
• List of Information Visualization projects
http://www2.iicm.edu/ivis/ivis/node1.htm
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (1)
Raw Data
Data
Data Tables
Data
Transformation
Visual Form
Visual Structures
Visual
Mappings
View
Transformations
Views
Task
Human Interaction
Víctor González ([email protected])
ICS 280: Information Visualization
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1
Mapping Data to Visual Form (2)
• Raw Data
- Data transformations map raw data, that is, data in some idiosyncratic
form, into Data Tables
- Numbers, texts, names, etc -> without structure
-> difficult to map to visual forms
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (3)
Raw Data
Data
Data Tables
Data
Transformation
Visual Form
Visual Structures
Visual
Mappings
View
Transformations
Views
Task
Human Interaction
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (4)
• Data Tables
- This tables are based on relational descriptions of data extended
through the use of metadata
Casei represents a unique object and the values represent characteristics
Case
Case i
Case j
Case k
...
Variable x
Value ix
Value jx
Value kx
...
Variable y
Value iy
Value jy
Value ky
...
...
...
...
...
...
The columns
Input
Metadata
Variables
variables
represent
are are
the
uniquely
cases,
divided
labels
sets
determine
for
into
ofthe
values
input
rows
the
and
for
and
output
each
outputs.
columns
of
variables
the variables
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (4)
• Data Tables
- This tables are based on relational descriptions of data extended
through the use of metadata.
- Dimensionality is used to refer to the number of input variables,
the number of output variables, both together, or even the number of
spatial dimension in the data.
- Variable types can be nominal, ordinal or quantitative.
- Errors or missing values and statistical calculations can add additional
information. Data tables often contain derived value or structure (e.g.
derive the mean [value], sort the variables [structure]).
- Data transformation can help to discovered patterns.
Víctor González ([email protected])
ICS 280: Information Visualization
1
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Mapping Data to Visual Form (5)
Raw Data
Data
Data Tables
Data
Transformation
Visual Form
Visual Structures
Visual
Mappings
View
Transformations
Views
Task
Human Interaction
Víctor González ([email protected])
ICS 280: Information Visualization
1
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Mapping Data to Visual Form (6)
• Visual Structures
- Visual Mappings transform data tables into visual structures.
- The structures combine spatial substrates, marks and graphical properties.
- A mapping is said to be expressive if all and only the data in the Data
Table are also represented in the Visual Structure.
- A mapping is said to be more effective if it is faster to interpret, can
convey more distinctions, or leads to fewer errors than some other
mapping (e.g. sine wave)
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (6)
• Gestalt laws - principles of organization
- There can be interaction among the visual coding of information.
- Part of the point of coding information visually is to produce patterns
that the eye detects from ensembles of components.
Gestalt principles
• Pragnanz
• Proximity
• Similarity
• Closure
The
tendency
objects
near
one
Elements
Neighboring
IfThe
Every
several
tendency
stimulus
are
stimuli
elements
more
pattern
likely
unite
are
are
presented
contours
to
is
grouped
seen
in
together,
groups
that
Elements
that
aretoof
moving
inform
the same
another
to
be
grouped
together
intoin
together
if
the
there
are
such
groups
very
is
awhen
way
aclose
tendency
appear
that
they
the
are
each
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to
resulting
potentially
see
other.
the
ortogether.
meaningful.
structure
form
connected
direction
seem
toto
be
grouped
a as
perceptual
bysuch
is
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asimple
way
or smoothly
that
asunit.
possible.
the similar
curving
items
lines.
are
grouped together.
• Good continuation
• Common fate
• Familiarity
Víctor González ([email protected])
ICS 280: Information Visualization
1
8
Mapping Data to Visual Form (7)
Raw Data
Data
Data Tables
Data
Transformation
Visual Form
Visual Structures
Visual
Mappings
View
Transformations
Views
Task
Human Interaction
Víctor González ([email protected])
ICS 280: Information Visualization
1
9
Mapping Data to Visual Form (8)
• Views
- View Transformations create Views of the Visual Structures by specifying
graphical parameters such as position, scaling, and clipping.
- The user can restrict the view to certain data ranges.
Víctor González ([email protected])
ICS 280: Information Visualization
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0
Mapping Data to Visual Form (8)
• Views
- Since spatial position is such a good encoding several techniques have
been developed to increase the amount of information that can be
encoded with it.
• Composition is the orthogonal placement of axes, creating a 2D metric
space.
• Alignment is the repetition of an axis at a different position in the space.
• Folding is the continuation of an axis in an orthogonal dimension.
• Recursion is the repeated subdivision of space.
• Overloading is the reuse of the same space for the same Data Table
see-soft
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (8)
• View Transformation
- View transformations interactively modify and augment Visual
Structures to turn static presentations into visualization by establishing
graphical parameters to create Views of Visual Structures.
Location probes
Location proves are view transformations that use location in a visual
structure to reveal additional Data Table Information. (filmfinder)
Viewpoint Controls
Use affine transformations to zoom, pan, and clip the viewpoint.
Víctor González ([email protected])
ICS 280: Information Visualization
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Mapping Data to Visual Form (9)
Raw Data
Data
Data Tables
Data
Transformation
Visual Form
Visual Structures
Visual
Mappings
View
Transformations
Views
Task
Human Interaction
Víctor González ([email protected])
ICS 280: Information Visualization
2
3
Multiplication
186
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