Information Visualization - Georgia Tech Sonification Lab -...

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Information Visualization Pictures worth 1000 words...

Transcript of Information Visualization - Georgia Tech Sonification Lab -...

Information Visualization

Pictures worth 1000 words...

Fall 2017 PSYCH / CS 6755 2

Agenda

ØInformation Visualization overviewv Definitionv Principlesv Examplesv Techniques

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Data, Data Everywhere

ØOur world is bustling in dataØComputers, internet and web have given

people more access to it (but it’s been here all along)

ØHow do we make sense of it?ØHow do we harness this data in decision-

making processes?

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Three Approaches

ØSoftware Agentsv Computational agent that carries out user’s

requestØData Mining

v Software that analyzes database and extracts “interesting” features

ØInformation Visualizationv Visual tools to help users better examine the

data themselves

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Atlanta Flight Traffic

AJC

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London Underground

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Underground Overlaid on London100% Veridical Display is not always the goal…(The real Thames is in dark blue)

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Napolean’s March

size of armydirection

latitudelongitude

temperaturedate

From E. Tufte The Visual Display of Quantitative Information

Minard graphic

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Information Visualization

ØWhat is “Information”?v Items, entities, things which do not have a

direct physical correspondencev Notion of abstractness of the entities is

important too

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Information Visualization

ØWhat is “visualization”?v The use of computer-supported, interactive

visual representations of data to amplify cognition.

• From [Card, Mackinlay Shneiderman ‘98]

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Information Visualization

ØEssence:v Taking items without a physical

correspondence and mapping them to a 2-D or 3-D physical space.

v Giving information a visual representation that is useful for analysis and decision-making

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Main Idea

Ø“The purpose of visualization is insight, not pictures”

ØVisuals help us thinkv External cognition v Provide a frame of reference, a temporary

storage area

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Domains for Info Vis

ØTextØStatisticsØFinancial/business dataØInternet informationØSoftwareØ...

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Components of Study

ØData analysisv Data items with attributes or variablesv Generate data tables

ØVisual structuresv Spatial substrate, marks, graphical properties

of marksØUI and interactionØAnalytic tasks to be performed

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Tasks in Info Vis 1ØSearch

v Finding a specific piece of information• How many games did the Braves win in 1995?• What novels did Ian Fleming author?

ØBrowsev Look over or inspect something in a more

casual manner, seek interesting information• Learn about crystallography• What has Jane been up to lately?

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Tasks in Info Vis 2

ØAnalysisv Comparison-Differencev Outliers, Extremesv Patterns

ØAssimilateØCategorizeØLocate

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Tasks in Info Vis 3

ØIdentifyØRankØAssociateØRevealØMonitorØMaintain awarenessØ...

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ExampleNYC weather

2220 numbersTufte, Vol. 1

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Example

Univ. of Maryland

Film Finder

Video

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InfoVis Techniques

ØAggregationv Accumulate individual elements into a larger

unit to be presented as some wholeØOverview & Detail

v Provide both global overview and detail zooming capabilities

ØFocus + Contextv Show details of one or more regions in a

more global context (eg, fisheye)

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InfoVis Techniques

ØDrill-downv Select individual item or smaller set of items

from a display for a more detailed view/analysis

ØBrushingv Select or designate/specify value, then see

pertinent items elsewhere on the display

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Mantra

ØOverview first, zoom and filter, then details on demand

-- Ben Shneiderman

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Issues

ØGraphic designv Extremely important in information

visualizationv Should reveal data and relationships, not

obscure themv Tufte books provide many guidelines

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Issues

ØScalabilityv Presentation of information becomes really

interesting as the size of the data growsv Run out of pixels at some pointv Requires aggregation, navigation, …

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Issues

ØInteractionv Computer provides interactive capability that

we do not have in printed pagev Often, must navigate and examine different

views of data to gain insight

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More Exampleshttp://www.smartmoney.com/marketmap

Demo

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More ExamplesData Mountain

Microsoft Research

Video

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Visualizing Hierarchies

ØVariety of techniquesv Traditional tree views, alternatives, space-

filling views

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Hierarchies

ØDefinitionv Ordering of items in which particular items

are parents or ancestors of others

ØExample: File Systemv Folders/Directories with

folders/subdirectories and files inside

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Trees

ØHierarchies often represented as treesØRoot at top, leaves at bottom

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Sample Representation

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Another Representation

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Another Representation

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Another Representation

root

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Another Representation

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Potential Problems

ØWidth of fan-out uses real estatev Run out of room quickly

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Another Idea

CHEOPS

Beaudoin, Parent & Vroomen

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Another Idea

Card, Mackinlay & Robertson

ConeTree

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Another Idea

ØUse hyperbolic geometryØHyperbolic tree

ØHere: Site Lens fromwww.inxight.com

ØDemo

Lamping & Rao

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Space-Filling Representation

Each item occupies an area

Children are “contained” under parent

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Treemap

ØSpace-filling representation developed by Shneiderman and Johnson

ØChildren are drawn inside their parentØAlternate horizontal and vertical slicing at

each successive level

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Treemap

File and directory visualizer

white-directoriescolor-files

level 1dirs

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Treemap

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Nested vs. Non-nested Treemaps

Nested Tree-Map Non-nested Tree-Map

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Treemap Affordances

ØGood representation of two attributes: color and area

ØNot as good at representing structurev What happens if it’s a perfectly balanced

tree of items all the same size?v Also can get long-thin aspect ratios

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Treemap Variation

ØSmartMoney.com Map of the Marketv Illustrates stock movementsv “Compromises” treemap

algorithm to avoid badaspect ratios

www.smartmoney.com/marketmap

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Treemap Variation

ØUse 3Dshadingcues tohelpconveystructure

SequoiaViewfile viewer forWindows

Demo

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Another Technique

ØWhat if we used a radial rather than a rectangular space-filling technique?

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Sunburst

Visualizing fileand directorystructures

Root dir at centerColor - file typeAngle - file/dir size

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Evaluation: Experiment

ØCompare Treemap and Sunburst with users performing typical file/directory-related tasks

ØEvaluate task performance on both correctness and time

Small Hierarchy(~500 files)

Large Hierarchy(~3000 files)

A B A B

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Experiment

Ø60 participantsØParticipant only works with a small or

large hierarchy in a sessionØVary order across participants

SB A, TM BTM A, SB BSB B, TM ATM B, SB A

32 on small hierarchies28 on large hierarchies

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Tasks• Identification (naming or pointing out) of a file based on size,

specifically, the largest and second largest files (Questions 1-2)• Identification of a directory based on size, specifically, the largest (Q3) • Location (pointing out) of a file, given the entire path and name (Q4-7) • Location of a file, given only the file name (Q8-9)• Identification of the deepest subdirectory (Q10)• Identification of a directory containing files of a particular type (Q11) • Identification of a file based on type and size, specifically, the largest

file of a particular type (Q12)• Comparison of two files by size (Q13)• Location of two duplicated directory structures (Q14)• Comparison of two directories by size (Q15)• Comparison of two directories by number of files contained (Q16)

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Results

ØOrdering effect for Treemap on large hierarchies

ØPerformance trends favored Sunburst, but not clear-cut

ØSubjective preference:SB (51), TM (9), unsure (1)

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Observations

ØSB appeared to convey structure betterØParticipants felt TM conveyed size better,

but not borne out in performanceØStrategies mattered

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SunBurst Negative

ØIn large hierarchies, files at the periphery are usuallytiny and verydifficult todistinguish

examples

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Fix: ObjectivesØMake small slices

biggerØMaintain full circular

space-filling ideaØAllow detailed

examination of small files within context of entire hierarchy

ØDon’t alter ratios of sizes

ØAvoid use of multiple windows or lots of scrollbars

ØProvide an aesthetically pleasing interface in which it is easy to track changes in focus

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Stasko & ZhangProceedings of Information Visualization 2000,Oct. 2000, pp. 57-65.

3 Solutions

ØThree visualization+navigation techniques developed to help remedy the shortcomingv Angular detailv Detail outsidev Detail inside

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Angular Detail

• Most “natural”• Least space-efficient• Most configurable by

user

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Detail Outside

• Exhibits non-distortedminiature of overview

• Somewhat visuallydisconcerting

• Focus is quite enlarged(large circumference and 360°)

• Relatively spaceefficient

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Detail Inside

• Perhaps least intuitiveand most distorting

• Items in overview aremore distinct (largercircumference)

• Interior 360° for focusis often sufficient

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Key Components

ØTwo ways to increase area for focus region: larger sweep angle and longer circumference

ØSmooth transitions between overview and focus allow viewer to track changes

ØAlways display overviewØAllow focus selections from anywhere:

normal display, focus or overview regions

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Good ReferencesBooks

Software Abounds

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ØIBM Many Eyeshttp://www-958.ibm.com/software/data/cognos/manyeyes/

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Interested in more...Course

ØCS 7450ØJohn StaskoØCourse foci

v Look at research ideas v Work with commercial systemsv Assignments and term project