CS 5764 Information Visualization

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CS 5764Information Visualization

• Dr. Chris North

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Today

• What is Information Visualization?
• Who cares?
• What will I learn?
• How will I learn it?

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1. What is Information Visualization?

• The use of computer-supported, interactive,
  visual representations of abstract data to
  amplify cognition
• Card, Mackinlay, Shneiderman

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The Big Problem

Human
Data
Data Transfer
How?

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The Big Problem
Human
Data
Data Transfer
How?
Vision Aural Smell Haptics Taste esp
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Human Vision

• Highest bandwidth sense
• Fast, parallel
• Pattern recognition
• Pre-attentive
• Extends memory and cognitive capacity
• (Multiplication test)
• People think visually
• Brain 8 lbs, vision 3 lbs
• Impressive. Lets use it!

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Find the Red Square
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Find the Red Square
Pre-attentive
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• Which state has highest Income? Avg?
  Distribution?
• Relationship between Income and Education?
• Outliers?

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College Degree
Per Capita Income
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Visual Representation Matters!

• Text vs. Graphics
• What if you could only see 1 states data at a
  time? (e.g. Census Bureaus website)
• What if I read the data to you?
• Graphics vs. Graphics
• depends on user tasks, data,

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History Static Graphics
Minard, 1869
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The Big Problem
Human
Data
Data Transfer
visualization
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The Bigger Problem
Data
Human
Data Transfer
interactive visualization
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Interactive Graphics

• Homefinder

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Search Forms

• Avoid the temptation to design only a form-based
  search engine
• More tasks than just search
• How do I know what to search for?
• What if theres something better that I dont
  know to search for?
• Hides the data
• Only supports QA
• How can search be integrating with
  visualization?

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User Tasks
Excel can do this

• Easy stuff
• Min, max, average,
• These only involve 1 data item or value
• Hard stuff
• Patterns, trends, distributions, changes over
  time,
• outliers, exceptions,
• relationships, correlations, multi-way,
• combined min/max, tradeoffs,
• clusters, groups, comparisons, context,
• anomalies, data errors,
• Paths,

Visualization can do this!
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More than just data transfer

• Glean higher level knowledge from the data
• Learn data ? insight

• Reveals data
• Reveals knowledge that is not necessarily
  stored in the data
• Insight!

• Hides data
• Hampers knowledge
• Nothing learned
• No insight

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Some Philosophy

• bigger picture Insight
• Vs. statistics, data mining,
• Formal vs informal
• even bigger Visual Analytics
• Interaction as central
• Perception -gt cognition
• Visualization in context

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Class Motto

• Show me the data!

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2. Who Cares?
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• Presentation is everything

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My Philosophy Optimization

• Computer
• Serial
• Symbolic
• Static
• Deterministic
• Exact
• Binary, 0/1
• Computation
• Programmed
• Follow instructions
• Amoral

• Human
• Parallel
• Visual
• Dynamic
• Non-deterministic
• Fuzzy
• Gestalt, whole, patterns
• Understanding
• Free will
• Creative
• Moral

• Visualization the best of both
• Impressive computation impressive cognition

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3. What Will I Learn?

• Design interactive visualizations
• Critique existing designs and tools
• Develop visualization software
• Empirically evaluate designs
• Understand current state-of-art
• An HCI focus
• A visualization a user interface for data

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Topics

• Information Types
• Multi-D
• 1D, 2D, 3D spatial
• Hierarchies/Trees
• Networks/Graphs
• Document collections
• Analytics
• Analytic theories
• Analytic methods

• Strategies
• Design Principles
• Interaction strategies
• Navigation strategies
• Visual Overviews
• Multiple Views
• Empirical Evaluation
• Development
• Theory
• High-Resolution Displays

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GigaPixel Display
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Related Courses

• Scientific Visualization (ESM4714)
• Computer Graphics (4204, 6xxx)
• Usability Engineering (5714)
• Research Methods (5014)
• Model Theories of HCI (5724)
• User Interface Software (5774)
• Info Storage Retrieval (5604)
• Databases (5614), Digital Libraries (6xxx)
• Data Mining (6xxx)

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4. How will I learn it?Course Mechanics

• http//infovis.cs.vt.edu/cs5764/
• Grading
• (See Syllabus online)
• Format
• Read research papers (see web site)
• In-class discussion
• Emphasis on project

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Research Class

• Creativity
• Open ended
• Often no right answer
• Reasoning/argument is more important
• Thinking deeply
• Self motivation, seek to excel
• Contribute to the state-of-the-art
• Jump start for thesis research, publication

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Project

• Groups of 4 students
• Visualization for Intelligence Analysis
• Milestones
• Team choose team (due Thurs!)
• Design Concept Presentation problem, lit.
  review, design, schedule (4 weeks)
• Initial implementation
• Complete implementation
• Evaluation
• Final presentation
• Final paper publishable?

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Project

• Groups of 3 students
• Categories
• Development design, implement, evaluate new
  visualization
• Evaluation empirical experiments with users
• Theory literature survey, synthesize theory or
  taxonomy
• Milestones
• Abstract choose team and topic (due next
  week!)
• Proposal problem, lit. review, design, schedule
• Mid-semester presentation initial results
• Final presentation final results
• Final paper publishable?

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Paper Presentations

• Each student gets 1 slot during semester
• Present a paper in class
• 15 minutes
• Show the demo/pictures/video
• Convey 1-2 main ideas
• How does it really help? Make a scientific
  argument
• Discuss

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Implementation detail crap

• The first step of processing requires the
  construction of several tree and graph structures
  to store the database.
• System then builds visualization of data by
  mapping data attributes of graph items to
  graphical attributes of nodes and links in the
  visualization windows on screen.
• More boring stuff nobody is ever going to read
  here or if they do they wont understand it anyway
  so why bother.
• If they do read it then they most certainly will
  not be listening to what you are saying so why
  bother give a talk? Why not just sit down and
  let everybody read your slides or just hand out
  the paper and then say thank you.
• This person needs to take Dr. Norths info vis
  class.

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Assignment
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Force Adds?

• Why?
• Academic goals?
• Can you keep up?