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CS 7450 Information Visualization

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Title: CS 7450 Information Visualization


1
Introduction
  • CS 7450 - Information Visualization
  • Aug. 24, 2000

2
Exercise
  • Picnic directions

3
Data Explosion
  • Society is more complex
  • There simply is more stuff
  • Computers, internet and web give people access to
    an incredible amount of data
  • news, sports, financial, purchases, etc...

4
Data Overload
  • Problem How to make use of the data
  • How do we make sense of the data?
  • How do we harness this data in decision-making
    processes?
  • How do we avoid being overwhelmed?

5
The Challenge
  • Transform the data into information
    (understanding, insight) thus making it useful to
    people

6
One Approach
  • Provide tools that present data in a way to help
    people understand and gain insight from it
  • Cliches
  • Seeing is believing
  • A picture is worth a thousand words

7
Exercise Redux
  • What did you put on your paper?
  • Text?
  • Pictures?
  • People work differently

8
Visualization
  • Often thought of as process of making a graphic
    or an image
  • Really is a cognitive process
  • Form a mental image of something
  • Internalize an understanding
  • The purpose of visualization is insight, not
    pictures
  • Insight discovery, decision making, explanation

9
Main Idea
  • Visuals help us think
  • Provide a frame of reference, a temporary storage
    area
  • External cognition
  • Role of external world in thinking and reason
  • Examples?

10
Information Visualization
  • What is information?
  • Items, entities, things which do not have a
    direct physical correspondence
  • Notion of abstractness of the entities is
    important too
  • Examples baseball statistics, stock trends,
    connections between criminals, car attributes...

11
Information Visualization
  • What is visualization?
  • The use of computer-supported, interactive visual
    representations of data to amplify cognition.
  • From Card, Mackinlay Shneiderman 98

12
What Its Not
  • Scientific Visualization
  • Primarily relates to and represents something
    physical or geometric
  • Examples
  • Air flow over a wing
  • Stresses on a girder
  • Weather over Pennsylvania

13
Information Visualization
  • Components
  • Taking items without a direct physical
    correspondence and mapping them to a 2-D or 3-D
    physical space.
  • Giving information a visual representation that
    is useful for analysis and decision-making

14
Two Key Attributes
  • Scale
  • Challenge often arises when data sets become very
    large
  • Interactivity
  • Want to show multiple different perspectives on
    the data

15
Domains for Info Vis
  • Text
  • Statistics
  • Financial/business data
  • Internet information
  • Software
  • ...

16
Examples
  • Images
  • Minivan comparison, Atlanta air traffic,
    London/Paris subways
  • Videos
  • Film Finder (Maryland)
  • Timelines (MIT)
  • Software (saw last time)
  • Map of the Market (SmartMoney)
  • SunBurst (GT)

17
Tasks in Info Vis
  • Search
  • Finding a specific piece of information
  • How many games did the Braves win in 1995?
  • What novels did Ian Fleming author?
  • Browsing
  • Look over or inspect something in a more casual
    manner, seek interesting information
  • Learn about crystallography
  • What has Jane been up to lately?

18
Tasks in Info Vis
  • Analysis
  • Comparison-Difference
  • Outliers, Extremes
  • Patterns
  • Assimilation
  • Monitoring
  • Awareness

19
Knowledge Crystallization
  • Information foraging
  • Search for schema (representation)
  • Instantiate schema
  • Problem solve to trade off features
  • Search for a new schema that reduces problem to a
    simple trade-off
  • Package the patterns found in some output product

From CMS 98
20
How Vis Amplifies Cognition
  • Increasing memory and processing resources
    available
  • Reducing search for information
  • Enhancing the recognition of patterns
  • Enabling perceptual inference operations
  • Using perceptual attention mecahnisms for
    monitoring
  • Encoding info in a manipulable medium

21
Process
task
Raw data
Data tables
Visual Structures
Views
Data transformations
Visual mappings
View transformations
22
Sources Used
  • CMS book
  • Spence book
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