22
Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Embed Size (px)

Citation preview

Page 1: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Analysis Experiences Using Information Visualization

Beth Hetzler

Alan Turner

Page 2: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Realizing Value from Visual Analysis Tools

Sound algorithms (representation, clustering, projection, etc.)

Visualization conveys useful informationInteraction natural and easy to learnUser able to profit from visualization (*)Concepts fit user model(s) and process (*)System works acceptably in user

environment (*)

Page 3: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Analysts’ Environment

Lots of information, variety of sources Constantly more new informationTime pressureDifficult to tell what is pertinent without

reading or skimmingMay be learning new subject areaMay not be expert in computer science

Page 4: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Analytic Environment (cont.)

Maintain expertise in particular areasbroad issues over timechanging vocabulary, evolving themes“Tyranny of the inbox”

Ad hoc questions on short fuselittle time to hone queries

Need to provide and support judgementRisks of satisficing

Page 5: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Analysts’ Dilemma

419 Query 2

24 on-topic

8 cut andpaste

2000 in Database

3 key

725 Query 1

6 High Profit

3 HighProfit

28 read

Participant 5: 96 minutesExperience: 17 yearsQuery 1: ESA | (european & space & agency)Query 2: (ESA | (european & space & agency)) > (19960601) Infodate

419

28

Key documents

Key documents that are high profit

High profit documents

Legend

©1999 Patterson

With permission of Emily Pattersonn

Page 6: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

S2: 73 minutesesa & ariane*(esa & ariane*) & failure

S3: 24 minuteseurope 1996(europe 1996) & (launch failure)(europe 1996) & ((launch failure):%2)

S4: 68 minutes(european space agency):%3 & ariane & failure & (launcher |rocket))

S6: 32 minutes1996 & Ariane(1996 & Ariane) & (destr* | explo*)(1996 & Ariane) & (destr* | explo*) & (fail*)

S7: 73 minutessoftware & guidance

S8: 27 minutesesa & arianeariane & 5(ariane & 5):%2((ariane & 5):%2) & (launch & failure)

S9: 44 minutes1996 & European Space Agency & satellite1996 & European Space Agency & lost1996 & European Space Agency & lost & rocket

161

29

22

5

169

15

S5: 96 minutesESA | (european & space & agency)(ESA | (european & space & agency)) > (19960601) Infodate

419

28

7

18466

14 12

194

4

29

Key documents Key documents that are high profitHigh profit documents

©1999 Patterson With permission of Emily Patterson

Page 7: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

What Could It Mean to “Address Information Overload?”

Reduce time spent crafting queriesReduce risk of eliminating important informationIncrease chance of recognizing important

informationAbility to handle more documentsImprove ability to structure information perusalReduce amount of readingFaster time to get through same information

Page 8: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

IN-SPIRE Basic Tools

ThemeView

Galaxy

DocumentViewer

TimeSlicer

Also: Query tool, Group tool, ...

Page 9: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Pilot Environment

Analysts in normal work environmentIN-SPIRE running on regular workstationAnalysts use as time allows, on questions

pertinent to their workNormal data, but alternate query toolAssess question most pertinent to analysts:

does it help me with my data and my issues?

Page 10: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Example User Value: Less Time on Query Syntax; Lower Risk of

Information Loss

Cricket-related

Data collection: news stories matching simple Boolean on Pakistan

Green dots: Documents that would be excluded by “not (cricket or wicket or champion*)”

Page 11: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Examples of User Value

Better structuring of daily reading material

Easier to identify non-relevant materialUseful information from speculative

large queriesThinking about the issue and information

in new ways

Page 12: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Examples of Issues

Novice vs. expert usage and benefitsGalaxy too staticClusters not relevant for some usersData glitches Pragmatics: print, save, ...

Page 13: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Adapting to User Process: New Analytic Feature

Common user processesLinear path through informationConvergent/divergent phases

Static visualization does not support well

Page 14: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Supporting Linear Path: Progressively Move Data Aside

Page 15: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Support Convergent/Divergent Process

Select or query to choose documents of interest

Move rest downInterest documents

recluster and reproject to show new themes

Move full set back up and repeat

Page 16: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Adapting to User Process: Interface to Legacy System

Conserve existing user query

Add additional broader one

Combine and show relationship

Smooth interface to current tools critical

Page 17: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Potential Tension: “Correct” vs. “Useful” Representations

Page 18: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Potential Tension: “Correct” vs. “Useful” Representations

Themes of interest may not be dominantnot dominant within data collectionnot dominant within documents

Users need way to “steer” to more interesting themes and relationships

Minimal demands on user inputClear that steering in effect

Page 19: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Support Analytic FlowResearch or monitoring

find important informationquicker process

Analysisconvergent/divergent thinkingidentify new hypotheses

Drafting/editing reportssummarize resultscapture citation, annotate, print

Page 20: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Bucket of Data Mismatch

Many tools work on fixed collectionUsers’ data is much more fluid

query results this morningmore documents this afternoonnew query term added

Users can’t afford to redo work

Page 21: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Data: the Good, the Bad, and the Ugly

Ideal is not real world

Tags in “wrong” place

Meta data within text

Missing field labels

“Is it useful on my data?”

Page 22: Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Conclusions

Information visualization can provide useful benefits for analysts

Need features to match user processNeed careful bridge to other user toolsAddress challenges, even if not central to

tool