Information Visualization for High Dimensional Data Ben Shneiderman - - PowerPoint PPT Presentation

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Information Visualization for High Dimensional Data Ben Shneiderman - - PowerPoint PPT Presentation

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Information Visualization for High Dimensional Data Ben Shneiderman ben@cs.umd.edu Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies

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Information Visualization for High Dimensional Data

Ben Shneiderman ben@cs.umd.edu

Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies

University of Maryland College Park, MD 20742

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Interdisciplinary research community

  • Computer Science & Psychology
  • Information Studies & Education

(www.cs.umd.edu/hcil)

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Scientific Approach (beyond user friendly)

  • Specify users and tasks
  • Predict and measure
  • time to learn
  • speed of performance
  • rate of human errors
  • human retention over time
  • Assess subjective satisfaction

(Questionnaire for User Interface Satisfaction)

  • Accommodate individual differences
  • Consider social, organizational & cultural context
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Design Issues

  • Input devices & strategies
  • Keyboards, pointing devices, voice
  • Direct manipulation
  • Menus, forms, commands
  • Output devices & formats
  • Screens, windows, color, sound
  • Text, tables, graphics
  • Instructions, messages, help
  • Collaboration & communities
  • Manuals, tutorials, training

www.awl.com/DTUI

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U.S. Library of Congress

  • Scholars, Journalists, Citizens
  • Teachers, Students
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Visible Human Explorer (NLM)

  • Doctors
  • Surgeons
  • Researchers
  • Students
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NASA Environmental Data

  • Scientists
  • Farmers
  • Land planners
  • Students
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Bureau of the Census

  • Economists, Policy

makers, Journalists

  • Teachers, Students
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NSF Digital Government Initiative

  • Find what you need
  • Understand what you Find

www.ils.unc.edu/govstat/

Census, NCHS,

BLS, EIA, NASS, SSA

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International Children’s Digital Library

www.childrenslibrary.org

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Piccolo: Toolkit for 2D zoomable objects

AppLens & Launch Tile

UMD, Microsoft Research

DateLens

Windsor Interfaces, Inc.

Cytoscape

Institute for Systems Biology Memorial Sloan-Kettering Institut Pasteur UCSD

TreePlus

UMD

Structured canvas of graphical objects in a hierarchical scenegraph

  • Zooming animation
  • Cameras, layers

Open, Extensible & Efficient Java, C#, PocketPC versions

www.cs.umd.edu/hcil/piccolo

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Information Visualization

The eye… the window of the soul, is the principal means by which the central sense can most completely and abundantly appreciate the infinite works of nature. Leonardo da Vinci

(1452 - 1519)

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Using Vision to Think

  • Visual bandwidth is enormous
  • Human perceptual skills are remarkable
  • Trend, cluster, gap, outlier...
  • Color, size, shape, proximity...
  • Human image storage is fast and vast
  • Opportunities
  • Spatial layouts & coordination
  • Information visualization
  • Scientific visualization & simulation
  • Telepresence & augmented reality
  • Virtual environments
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Information Visualization: US Research Centers

  • Xerox PARC
  • 3-D cone trees, perspective wall, spiral calendar
  • table lens, hyperbolic trees, document lens
  • Univ. of Maryland
  • dynamic queries, range sliders, starfields,

treemaps, timeboxes, zoombars

  • tight coupling, dynamic pruning, lifelines
  • IBM, Microsoft, AT&T
  • Georgia Tech, MIT Media Lab
  • Univ. of Wisconsin, Minnesota,

Calif-Berkeley, CMU

  • Pacific Northwest National Labs
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www.mayaviz.com

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www.ilog.com

Visualization Toolkits Visualization Toolkits

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Information Visualization: Mantra

  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
  • Overview, zoom & filter, details-on-demand
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Information Visualization: Data Types

  • 1-D Linear

Document Lens, SeeSoft, Info Mural, Value Bars

  • 2-D Map

GIS, ArcView, PageMaker, Medical imagery

  • 3-D World

CAD, Medical, Molecules, Architecture

  • Multi-Var

Parallel Coordinates, Spotfire, XGobi, Visage, Influence Explorer, TableLens, DEVise

  • Temporal

Perspective Wall, LifeLines, Lifestreams, Project Managers, DataSpiral

  • Tree

Cone/Cam/Hyperbolic, TreeBrowser, Treemap

  • Network

Netmap, netViz, SeeNet, Butterfly, Multi-trees

(Online Library of Information Visualization Environments)

  • tal.umd.edu/Olive

InfoViz SciViz .

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Treemap: view large trees with node values

+ Space filling + Space limited + Color coding + Size coding

−Requires learning

(Shneiderman, ACM Trans. on Graphics, 1992 & 2003)

TreeViz (Mac, Johnson, 1992) NBA-Tree(Sun, Turo, 1993) Winsurfer (Teittinen, 1996) Diskmapper (Windows, Micrologic) SequoiaView, Panopticon, HiveGroup, Solvern Treemap4 (UMd, 2004)

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Treemap: Stock market, clustered by industry

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www.hivegroup.com

Treemap: Newsmap

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Treemap: Gene Ontology

http://www.cs.umd.edu/hcil/treemap/

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www.hivegroup.com

Treemap: Product catalogs

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LifeLines: Patient Histories

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LifeLines: Customer Histories

Temporal data visualization

  • Medical patient histories
  • Customer relationship

management

  • Legal case histories
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Temporal Data: TimeSearcher 1.3

  • Time series
  • Stocks
  • Weather
  • Genes
  • User-specified

patterns

  • Rapid search
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Temporal Data: TimeSearcher 2.0

  • Long Time series (>10,000 time points)
  • Multiple variables
  • Controlled precision in match

(Linear, offset, noise, amplitude)

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Goal: Find Features in Multi-Var Data

  • Clear vision of what the data is
  • Clear goal of what you are looking for
  • Systematic strategy for examining all views
  • Ranking of views to guide discovery
  • Tools to record progress & annotate findings
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Multi-V: Hierarchical Clustering Explorer

www.cs.umd.edu/hcil/hce/ “HCE enabled us to find important clusters that we didn’t know about.”

  • a user
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Do you see anything interesting?

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What features stand out?

Sc atte r Plo t I

  • nization Energy
50 75 100 125 150 175 200 225 250 10 20 30 40 50
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Correlation…What else?

Sc atte r Plo t I

  • nization Energy
50 75 100 125 150 175 200 225 250 10 20 30 40 50
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… and Outliers

Sc atte r Plo t I

  • nization Energy
50 75 100 125 150 175 200 225 250 10 20 30 40 50

He Rn

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Demonstration

  • US counties census data
  • 3138 counties
  • 14 dimensions : population density, poverty

level, unemployment, etc.

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Rank-by-Feature Framework: 1D

Ranking Criterion

Rank-by-Feature Prism Score List Manual Projection Browser

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Rank-by-Feature Framework: 2D

Ranking Criterion

Rank-by-Feature Prism Score List Manual Projection Browser

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Ranking Criterion: Pearson correlation (0.996, 0.31, 0.01, -0.69) Ranking Criterion: Uniformity (entropy) (6.7, 6.1, 4.5, 1.5)

A Ranking Example

3138 U.S. counties with 17 attributes

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HCE Status

  • In collaboration and

sponsored by Eric Hoffman: Children’s National Medical Center

  • Phd work of Jinwook Seo
  • 72K lines of C++ codes
  • 4,000+ downloads since

April 2002

  • www.cs.umd.edu/hcil/hce
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Network Data

  • Nodes & Links
  • Relationships & communication
  • Scientific/legal citations
  • Difficult to complete tasks
  • Occlusion
  • Complexity
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Network Data

Network Visualization with Semantic Substrates

  • Meaningful

layout of nodes

  • User controlled

visibility of links

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Network Data

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Take Away Message

Rank-by-Feature Framework

  • Decomposition of complex problems

into multiple simpler problems wins

  • Ranking guides discovery
  • Systematic strategies

www.cs.umd.edu/hcil/hce

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www.cs.umd.edu/hcil

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6th Creativity & Cognition Conference

  • Washington, DC June 13-15, 2007
  • Receptions at Nat’l Academy of Sciences

& Corcoran Gallery of Art

  • Expand community of researchers
  • Bridge to software developers
  • Encourage art & science thinking

www.cs.umd.edu/hcil/CC2007

http://www.cs.umd.edu/hcil/CC2007/