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Title: Vis%202003%20%20MyLifeBits%20Challenge%20for%20Visualization%20Visualization:%20


1
Vis 2003 MyLifeBits Challenge for
VisualizationVisualization Form follows
function Visualization Science? Engineering?
Or Art?
  • Seattle, WA
  • 22 October 2003Gordon Bell
  • Microsoft Research

2
Notes for talk
  • Will the Grid help visualization? Access Grid.
    By more isolation?
  • Will going big help? Is there trickle down?
  • Graphics always intriguing
  • Does it scale?
  • An apology 950K for data visualization Google
    878K
  • Any way to do the computing nvidia
  • Large screens?
  • 3D over the horizondoes it get us anywhere?
  • http//www.math.yorku.ca/SCS/Gallery/
  • http//www.otal.umd.edu/Olive/
  • MyLifeBiits live forever, timeline,
    relationships,

3
My affair with Visualization
  • 1958 wrote programs that displayed on the 32x32
    scrolling display of Deuce, a machine that came
    from NPL that Turing worked on. Interactive
    Marriage proposal program.
  • 1959 MIT Speech Lab and TX-0 10 1K x 1K points,
    basis for DEC display. Displayed sliders,
    sonograms, traditional engineering graphs. Made
    a Land use map of Boston for Gwen Bell, a student
    at Harvard School of Design. They later formed
    the Graphics lab or such displays.
  • 1960 DEC. Type 30 . Spaceware was built on it,
    but at one of the joint computer conferences, Ed
    Jacks of GM watched the display the whole time
    and got IBM to build them displays for car
    design.
  • 1961 saw the difference of logic diagrams vs.
    logic equations i.e. east vs west coast design
  • 1986-1989 DanagtArdentgtStardent the graphics
    supercomputer.
  • 1987 Commissioned the NSF Study for
    visualization.
  • 1987 FCCSET report for the Internet proposal
    claimed we need the net for visualization.
  • 1990 Keynoted first visualization conference in
    SF. Met the Fakespace team and became an
    investor. They produced the boom for VR, large
    scale displays, tables, etc.

4
Outline
  • Now I find I was doing interactive vis in 1958.
  • Review of Vis 1990 keynote
  • Visualization (Google) 7M 4.4M data
  • Vis 1990 then and now
  • Shneiderman, Tufte, examples
  • Can you help MyLifeBits?
  • Timelines
  • Document knowledge management

5
1987 FCCSET Report for NREN
6
Titan Graphics Supercomputer c1988 25Kpolygons/sec
7
Keynote from Visualization I.23 October 1990
  • Or how I saw it then before the web, but after
    NREN (Internet.)

8
How I "See" saw Visualization 13 years ago
  • The Turing TEST for Visualization 3D, dynamic
    computer graphics and computer imaging are aimed
    at photo realism, ... i.e. the standard of
    comparison is limited by a view or photo of the
    phenomenon itself (reality).
  • The insight comes from within the
    user.Technology helps somewhat in the viewing.
  • Few of today's vizs provide the insight that
    compare with the creative representations that
    Tufte collected.
  • Challenge Make the computer do what the artists
    did!
  • Users need Vizicalcs (otherwise everything is a
    creation)
  • Training and integration into the computing
    mainstream is still the bottleneck to use
  • form mental image of something not visible

9
Computation is the Driving Force for
Visualization
  • 4. Analysis-by-synthesis in a real time
    environment
  • Real, experimental science that simulates and
    simultaneously compares observations. Courtesy of
    Web Services
  • 3. Simulation is the Third Paradigm of Science
    Engineering, after
  • 2. Experimentation (taking and plotting data) and
  • 1. Theory
  • 0. Talk is for philosophers
  • The best way to advance a science is by building
    a computer (i.e. program) for that phenomenon in
    an "analysis-by-synthesis" fashion.
  • Viz has come about through integrated computation
    and graphics, with a push from supercomputing.

10
The NSF Visualization Report Domain Needs
  • Steer simulation and computation
  • W/S driven use of supers
  • Graphics-oriented programming environments
  • Higher-order viz of scalar, vectors ... tensor
    fields
  • Dynamic viz of fields and flows
  • Massive data sets for signals and images
  • Algorithms and archs for parallel graphics IP
  • Framework for international Viz standards

11
The NSF Visualization Report (Cited) Benefits
  • Integrated set of portable tools
  • Scientific progress and leadership
  • Scientific productivity
  • Standardization of research tools and the
    cross-discipline flow of knowledge
  • Safeguard American Industrial Competitiveness
  • Making the Advanced Supercomputing facilities
    useful

12
Any Effect of the NSF Visualization Report?
  • Raised awareness of the opportunity for Viz by
    creating a word and focus
  • Got funding at various centers (e.g. UC/SD)
  • Galvanized a collection of people working in the
    area
  • ...
  • Ultimately stimulated this conference a year or
    two before it might have otherwise happened
  • Reaction to size and lack of applications focus
    at SIGGRAPH

13
Searching for Vizicalc"have data, need a
picture"
  • Users wanted to visualize their datahow much
    and how fast can it be displayed? how long to
    get the first picture?
  • Applications done on ad hoc case at a time basis
  • New tools such as AVS came about because of
    limited resources that had to apply the first
    graphics supercomputers.

14
Searching for Visualization
  • How do you get knowledge from data or a model?1.
    Who is the user?2. What is the cost (time to
    first pix, time/pix)3. What is benefit for
    various cost levels?
  • Standards, (part of "print" statement ... only
    hope is a Vizicalc. Wait for the PC to get it.
  • Training and adoption into various curricula
  • Can the CG IP techniques be given back to
    Siggraph so that Vizgraph works on visualization?
  • Move to explore techniques and fundamentals of
    Viz. Implies wide ranging application focus.
  • Codification and encapsulation of Viz methods
    into program packages to advance Viz more rapidly

15
Progress 1990 - 2003
  • The big bang Internet and the web
  • 1987 FCCSET Report set fiber goal by 2000
  • Moores Law
  • 10s of Mips gtgt 1-4 Gips Custom rendering
  • 10s of Mbytes gtgt 100 Gbytes
  • 25 K polygons/sec gtgt 25 M polygons/sec
  • Mpixels Mpixels mono but lower cost
  • 1.5 Mbps gt 1-2 Gbps (peak)
  • Progress in Vis
  • Realistic rendering see complete virtual
    scenes/sets
  • Expensive, large screens and caves
  • Using 2001, A Space Odyssey progress in
  • Visualization was much, much greater
  • AI, including speech was much, much less

16
Princeton 6K x 3K pixel 18x8 100K
17
Vis 2003
  • Problem and opportunity
  • have many nouns
  • Needcreate verbs

18
Taxonomy
  • Pseudo phenomena (ICs, molecules, colored
    physical parameters e.g. T, p, fields for flow,
    stress
  • Photo realism
  • Real world movies, VR, Augmented Reality,
  • People and digital immortality
  • Telepresence ever emerging, potentially
    important
  • Data visualization Tufte gallery candidates?
  • Small no. of dimensions
  • Large dimensionality information maps
  • Ordinary text and user visualization beyond UI

19
Shneidermans insights
  • exploratory data analysis and visualization
    process is characterized by mantra for visual
    information seeking
  • Overview, zoom and filter, details-on-demand
  • The future larger, higher resolution screens,
    that present perceptually-rich
    information-abundant displays. the flood of
    information can be turned into a river of
    knowledge...Human perceptual skills are quite
    remarkable and largely underutilized

20
Tufte on Graphic Excellence
21
Tufte
22
Tufte Napoleon Map Paris-Moscow
23
Data maps near and dear
24
Network flow of trade
25
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26
Hillis Taxonomy
27
Axon
28
Kiviat/radar of car parameters
29
Evolution of the Ideal State at Each Stage
Entrepreneurials
Stage IV.
Market Development
Business Plan
Stage III.
Manufacturing
Marketing
Product Development
Product
Stage II.
Development
Seed
Sales
Stage I.
Concept
Technology/
CEO
Engineering
Team
Control
Fundability
Board of Directors
Cash
30
Many dimensions.. Inverse pattern recognition
31
Tufte On
PowerPoint
32
I am data
33
The guinea pig
  • Gordon Bell is digitizing his life
  • Has scanned/encoded virtually all
  • All computer files
  • Personal documents (memos and email, bills,
    legal documents, papers written, )
  • Books written (and read when possible)
  • Photos
  • Posters, paintings, photo of things (artifacts,
    medals, plaques)
  • CD collection
  • Home movies and videos
  • Now recording real time phone, radio, TV
    (movies), web pages started meetings,
    conversations to come
  • Paperless throughout 2002. 12 scanned, 12
    discarded.
  • Only 30 GB!!!

34
The MyLifeBits Challenge
  • Files, photos, documents
  • Challenge is viz relevant for organizing,
    searching, and utilizing your shoebox data
    problem
  • Tufte vs. Visioneers
  • Visualization is an art.
  • Visualization is science and it has to be
    automatic!
  • Challenge
  • 1. What are the questions viz can help answer?
  • 2. What viz can help make a life or after life
    interesting?
  • We have many nouns. You make verbs.

35
Statistics of use
36
Visualization Needs Possibilities
  • Time lines
  • Video cliplets, photos searching
  • Automatic story creation from content
  • Related document maps
  • Concept mapping of entire space
  • Collections taxonomies
  • Synthesis of talking heads in their words
  • Tweening from photos to recreate entire movies of
    the experience.

37
Personal LifeLog Applications
Diary/Journal
Self
Tutor
Mentor
Advisor
Meeting Prep
Personal Assistant
Babysitter
Financial Manager
Companion Caretaker
Medical Manager
Parole Officer
Photo Album
Assistant for Elderly
Application used by
Pers Flight Recorder
Autobiography
Captains Log
Conservator
Biography
Baby Book
Trustee
Obituary
Personal Proxy
Executor
Others
Application controlled by
Others
Self
38
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39
MyLifeBits organization time and space
Archival (time) Working
Timeline/ Context(space)
Personal (some s) GB Co.(angel, etc.)
Professional ACM, etc., _at_Microsoft.com, New
cos.
40
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990
2000 2010 C,L m
d d CGB... GB SR mB,L
KF SB Where KvMO B ABos
P B WCa 6-year
--GS-HS--MIT DEC---.--- Education
KV-----mit,F cmu Work Bell
Elec DECcmuDEC E,NSF MSFT ComputerMuseum
M B SiValley Books
BN SBN
HiTechVent Computers 4-6
11 VAX E T Awards..

41
Time-machine ComputingRekimoto
42
Lifestreams View by timeDavid Gelernter et al
43
Rock Roll History graph
44
Timeline view tells a story
45
MyLifeBit v2 clustered time view
46
Information Visualization within a Digital Video
Library
  • Colored notches show where matches occur

47
Information Visualization within a Digital Video
Library
  • Keyword color matches color in ranking

48
Here are the photos
49
Getting the user to tell a story is the ultimate
in media value
  • A story is a layout in time and space
  • Most valuable content (by selection, and by being
    well annotated)
  • Stories must include links to any media they use
    (for future navigation/search transclusion).
  • Cf MovieMaker Creative Memories PhotoAlbums

We took him to lunch at our favorite Dim Sum
place to say farewell
Dapeng was an intern at BARC for the summer of
2000
At table L-R Dapeng, Gordon, Tom, Jim, Don,
Vicky, Patrick, Jim
50
Digital Immortality CMU Interactive Einstein
51
U of MD display of health data
52
http//www.research.ibm.com/history/gallery.htm
Document Changes History Flow
53
Temporal Analytics - ThemeRiver
  • Challenge identify patterns, trends, and
    relationships over time in large data collections
  • Breakthrough show change over time using smooth,
    stacked curves to enhance understanding include
    context of external events.

54
Haystack Ozone interface screenshot
  • Portal
  • Agents construct each window

55
Detail view
56
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57
Information Visualization within a Digital Video
Library
  • Christel Martin (CMU), Information
    Visualization within a Digital Video Library,
    Intelligent Information Systems, June 1998.

58
Inxight VizServer
http//www.inxight.com/map/
59
More inxight
60
Engineered for broad deployment Now under pilot
evaluation and deployment Windows based
client/server, stand alone, or web based
61
Towards Multiple Simultaneous Hypothesis Queries
Each Hypothesis on a Ray
  • Challenge
  • Multiple hypothesis analysis
  • Breakthrough
  • Interactive and visual method for analysis of
    multiple hypothesis
  • Impact
  • First example of hypothesis and scenario based
    analytics

62
Visualizing document relationshipsBoyack, Wylie
Davidson
63
WebScout (MSR Cambridge)
64
Clustered browsingof the Fine Arts Museum of San
Francisco
  • http//www.cs.berkeley.edu/kobus/research/project
    s/browse.html

65
The brain
66
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67
The Axon Idea processor
  • ..\..\Cyberall MyLifeBits\Axon Idea Processor.mht

68
Mind mapping
69
Innolab 3D File manager
70
Webmap
71
Webmap
http//www.webmap.com/trademapdemo.html
72
(No Transcript)
73
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74
Smartmoney.com
75
Smartmoney.com Whole market
76
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77
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78
State of a computer system
79
The end
80
The Evolution of Viz, i.e. Computer Graphics and
Image Processing, Technology
  • Coloring a "view" of an object according to some
    value (e.g. temperature) is gt1000 years old
  • Computer points gt wire frames gt 3D gt photo
    realism
  • Transparency for plotting data about a 3D point
    and to provide more views (Ds), including inner
    views-dynamics slow motion, particle traces,
    etc.
  • Analysis-by-synthesis using a computer generated
    model with which to compare real data - with
    added virtual reality worlds
  • Vizicalcs for user-defined visualization

81
The Levels of Visualization
  • How is a Viz used? How is a Viz created?
  • Computer app progmr Application/system
    Interactive data viewing Interactive data Viz
  • User/system builder Self
  • Peer and publications "
  • Congressional CSs, Artists, ... Vizineersand
    Siggraph

82
The NSF Visualization Report (11/87)
Recommendations
  • Short Term Long Term
  • Users to use (e.g. W/S) to use
  • Tool builders - to develop model
    Viz-environments
  • Method of computing ... to observe simulation
    and computation. both image understanding
    synthesis
  • Unify computer graphics, image processing,
    computer vision, CAD, signal processing, and user
    interface studies

83
The NSF Visualization Report Limits
  • Out of balance funding at all 3 levels too much
    data is generated and not viewed, too much and
    too little equipment, too little software, and
    no support for Viz
  • Network speed and ability to do televisualization
    (Televiz)
  • Training and support of computational scientist
    and engineers are needed
  • Standards are nil

84
The Evolution of Viz, i.e. Computer Graphics and
Image Processing, Technology
  • 1970s Core, GKS, Phigs - flexible, gets at the
    system, but difficult to use
  • 1980s Plot10, specials applications, unique
    libraries - expensive, low volume, single
    discipline (not generalizable), can't exploit
    hardware
  • 1990s AVS, apE, Foto, Spy Glass, Wavefront

85
What AVS is Beginning to Achieve
  • Provide application with the system's power as
    measured by bandwidth, processing viewing
  • Support and unify geometric, image and volume viz
  • Point and click, interactive data-flow
    programming
  • Framework using objects to minimize programming
  • Community of ever increasing application modules
    ... a library on which others can use and build
  • Horizontal and vertical platform standardization
  • Is used by scientist/engineer ... application
    engineer
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