Analysis Experiences Using Information Visualization Beth Hetzler Alan Turner

Realizing Value from Visual Analysis Tools Sound algorithms (representation, clustering, projection, etc.) Visualization conveys useful information Interaction natural and easy to learn User able to profit from visualization (*) Concepts fit user model(s) and process (*) System works acceptably in user environment (*)

Analysts’ Environment Lots of information, variety of sources Constantly more new information Time pressure Difficult to tell what is pertinent without reading or skimming May be learning new subject area May not be expert in computer science

Analytic Environment (cont.) Maintain expertise in particular areas broad issues over time changing vocabulary, evolving themes “Tyranny of the inbox” Ad hoc questions on short fuse little time to hone queries Need to provide and support judgement Risks of satisficing

Analysts’ Dilemma 419 Query 2 24 on-topic 8 cut and paste 2000 in Database 3 key 725 Query 1 6 High Profit 3 High Profit 28 read Participant 5: 96 minutes Experience: 17 years Query 1: ESA | (european & space & agency) Query 2: (ESA | (european & space & agency)) > ( ) Infodate Key documents Key documents that are high profit High profit documents Legend ©1999 Patterson With permission of Emily Pattersonn

S2: 73 minutes esa & ariane* (esa & ariane*) & failure S3: 24 minutes europe 1996 (europe 1996) & (launch failure) (europe 1996) & ((launch failure):%2) S4: 68 minutes (european space agency):%3 & ariane & failure & (launcher |rocket)) S6: 32 minutes 1996 & Ariane (1996 & Ariane) & (destr* | explo*) (1996 & Ariane) & (destr* | explo*) & (fail*) S7: 73 minutes software & guidance S8: 27 minutes esa & ariane ariane & 5 (ariane & 5):%2 ((ariane & 5):%2) & (launch & failure) S9: 44 minutes 1996 & European Space Agency & satellite 1996 & European Space Agency & lost 1996 & European Space Agency & lost & rocket S5: 96 minutes ESA | (european & space & agency) (ESA | (european & space & agency)) > ( ) Infodate Key documents Key documents that are high profit High profit documents ©1999 Patterson With permission of Emily Patterson

What Could It Mean to “Address Information Overload?” Reduce time spent crafting queries Reduce risk of eliminating important information Increase chance of recognizing important information Ability to handle more documents Improve ability to structure information perusal Reduce amount of reading Faster time to get through same information

IN-SPIRE Basic Tools ThemeView Galaxy Document Viewer Time Slicer Also: Query tool, Group tool,...

Pilot Environment Analysts in normal work environment IN-SPIRE running on regular workstation Analysts use as time allows, on questions pertinent to their work Normal data, but alternate query tool Assess question most pertinent to analysts: does it help me with my data and my issues?

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*)”

Examples of User Value Better structuring of daily reading material Easier to identify non-relevant material Useful information from speculative large queries Thinking about the issue and information in new ways

Examples of Issues Novice vs. expert usage and benefits Galaxy too static Clusters not relevant for some users Data glitches Pragmatics: print, save,...

Adapting to User Process: New Analytic Feature Common user processes Linear path through information Convergent/divergent phases Static visualization does not support well

Supporting Linear Path: Progressively Move Data Aside

Support Convergent/Divergent Process Select or query to choose documents of interest Move rest down Interest documents recluster and reproject to show new themes Move full set back up and repeat

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

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

Themes of interest may not be dominant not dominant within data collection not dominant within documents Users need way to “steer” to more interesting themes and relationships Minimal demands on user input Clear that steering in effect

Support Analytic Flow Research or monitoring find important information quicker process Analysis convergent/divergent thinking identify new hypotheses Drafting/editing reports summarize results capture citation, annotate, print

Bucket of Data Mismatch Many tools work on fixed collection Users’ data is much more fluid query results this morning more documents this afternoon new query term added Users can’t afford to redo work

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?”

Conclusions Information visualization can provide useful benefits for analysts Need features to match user process Need careful bridge to other user tools Address challenges, even if not central to tool