![LIFELINES
D
SINGLE RECOR
[Plaisant et al. 1998]
http://www.cs.umd.edu/hcil/lifelines](https://image.slidesharecdn.com/hcilsymp2010share-111127213915-phpapp02/75/finding-patterns-in-temporal-data-6-2048.jpg?cb=1668290292)
![LIFELINES 2
RECORD
D
R ECOR
RECORD
RECORD
RECORD
[Wang et al. 2008, 2009]
http://www.cs.umd.edu/hcil/lifelines2](https://image.slidesharecdn.com/hcilsymp2010share-111127213915-phpapp02/75/finding-patterns-in-temporal-data-11-2048.jpg?cb=1668290292)
![SIMILAN
RECORD
D
R ECOR
RECORD
RECORD
RECORD
[Wongsuphasawat & Shneiderman 2009]
http://www.cs.umd.edu/hcil/similan](https://image.slidesharecdn.com/hcilsymp2010share-111127213915-phpapp02/75/finding-patterns-in-temporal-data-15-2048.jpg?cb=1668290292)
![VISUALIZE
• Inspired by the Icicle tree [Fekete 2004]
Number of files!](https://image.slidesharecdn.com/hcilsymp2010share-111127213915-phpapp02/75/finding-patterns-in-temporal-data-26-2048.jpg?cb=1668290292)
Finding Patterns in Temporal Data
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Talk given at the 27th HCIL Annual Symposium, University of Maryland, College Park, MD, USA.
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Finding Patterns in Temporal Data
- 1. FINDING PATTERNS IN TEMPORAL DATA osium! CI L Symp KRIST WONGSUPHASAWAT 27th H 010! , 2 May 27 TAOWEI DAVID WANG CATHERINE PLAISANT BEN SHNEIDERMAN HUMAN-COMPUTER INTERACTION LAB UNIVERSITY OF MARYLAND
- 2. FINDING PATTERNS IN TEMPORAL DATA osium! CI L Symp KRIST WONGSUPHASAWAT 27th H 010! , 2 May 27 TAOWEI DAVID WANG CATHERINE PLAISANT BEN SHNEIDERMAN HUMAN-COMPUTER INTERACTION LAB UNIVERSITY OF MARYLAND
- 3. TEMPORAL CATEGORICAL DATA • A type of time series Event! Category! Event! Numerical! Stock: Microsoft Patient ID: 45851737 $'#")#"$!$&!$($$ &0!B$0& !"#$"#"$$%&!'(") &*++,-./& $'#")#"$!$&!$(!; &0!B$!& !"#$"#"$$%&!'(0) &123+43567& $'#")#"$!$&!$(0$ &0!B$"& !"#$"#"$$%&""('' &89:& $'#")#"$!$&!$('; &0!B$%& !"#$;#"$$%&$;($< &=/>>+& $'#")#"$!$&!!($$ &0!B!)& !"#!'#"$$%&$)(!? &1@,A& & Time Arrival Emergency ICU Floor Exit
- 4. TEMPORAL CATEGORICAL DATA Electronic Health Records: symptoms, treatment, lab test" Traffic incident logs: arrival/departure time of each unit" Student records: course, paper, proposal, defense, etc." " Others: web logs, usability study logs, etc."
- 5. 10+ years work on temporal visualization (mostly on Electronic Health Records)
- 6. LIFELINES D SINGLE RECOR [Plaisant et al. 1998] http://www.cs.umd.edu/hcil/lifelines
- 7. LifeLines – Single Patient
- 8. working with physicians at WASHINGTON HOSPITAL CENTER
- 9. EXAMPLE DATA • Patient transfers ARRIVAL Arrive the hospital EMERGENCY Emergency room ICU Intensive Care Unit INTERMEDIATE Intermediate Medical Care FLOOR Normal room EXIT-ALIVE Leave the hospital alive EXIT-DEAD Leave the hospital dead
- 10. TASKS • Example: Finding “Bounce backs” ICU Floor ICU within 2 days
- 11. LIFELINES 2 RECORD D R ECOR RECORD RECORD RECORD [Wang et al. 2008, 2009] http://www.cs.umd.edu/hcil/lifelines2
- 12. Multiple Records ARF (Align-Rank-Filter) Framework Temporal Summary LifeLines2 – Search and Visualize
- 13. ALIGNMENT • Sentinel events as reference points Time June July August Patient #45851737 Arrival Emergency ICU Floor Exit Patient #43244997 Arrival Emergency ICU Floor Exit
- 14. ALIGNMENT (2) • Time shifting Time 0 1M 2M Patient #45851737 Admit Emergency ICU Floor Exit Patient #43244997 Admit Emergency ICU Floor Exit
- 15. SIMILAN RECORD D R ECOR RECORD RECORD RECORD [Wongsuphasawat & Shneiderman 2009] http://www.cs.umd.edu/hcil/similan
- 16. Similan – Search by Similarity
- 17. Similan – Search by Similarity
- 18. FINDING “BOUNCE BACKS” Before After • Much faster to specify new query • Visualizing the results gives better understanding
- 19. USER STUDIES: SEARCH LifeLines2 Similan Exact! Similarity-based! MUST have A, B, C SHOULD have A, B, C Query Query Record#2 Record#2 more Record#1 Record#1 similar Record#3 Record#3
- 20. USER STUDIES: SEARCH LifeLines2 Similan Exact! Similarity-based! MUST have A, B, C SHOULD have A, B, C Query Query 1 Record#2 Record#2 more Record#1 Record#1 similar Record#3 Record#3
- 21. NEW STUFF Needs for an overview -> LifeFlow!!
- 22. TASKS • Example: Finding “Bounce backs” ICU Floor ICU within 2 days • Other questions Arrival ? ICU ? ?
- 23. LIFEFLOW RECORD D VISUALIZE R ECOR RECO Display the aggregation RD RECORD RECORD RECORD RECORD RECORD AGGREGATE Merge multiple records into tree
- 24. AGGREGATE • Aggregate by prefix #1 #2 #3 #4 Example with 4 records
- 25. AGGREGATE • Aggregate by prefix #1 #2 #3 #4
- 26. VISUALIZE • Inspired by the Icicle tree [Fekete 2004] Number of files!
- 27. VISUALIZE (2) • Use horizontal axis to represent time • Video
- 28. DEMO – LIFEFLOW When the lines are combined into flow!
- 29. FUTURE WORK • Comparison ICU ICU Intermediate Intermediate Jan-Mar 2008 April-June 2008 Floor
- 30. TAKE-AWAY MESSAGE Information visualization is a powerful way to explore temporal patterns. You can work with us on new case studies.