LifeFlow: Understanding Millions of Event Sequences in a Million Pixels
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LifeFlow: Understanding Millions of Event Sequences in a Million Pixels Presentation Transcript

  • 1. event event event event eventevent event event LIFE event event event event event event event event
  • 2. Time Event type ( 7:00 am, Wake up ) event event event event eventevent event event LIFE event event event event event event event event
  • 3. event event event event eventevent event event LIFE event event event event event event event event “Event Sequence”
  • 4. Human Activities( 7:00 am, Wake up ) ( 7:10 am, Shower ) ( 7:30 am, Breakfast )
  • 5. Traffic Incidents Logs( 9:30 am, Notification ) ( 9:55 am, Units arrived) ( 10:30 am, Scene cleared )
  • 6. Event Sequences Human Activities Electronic Health Records Traffic Incident Logs Usability Study Logs Web logs and more…
  • 7. Physicians atWashington Hospital Center
  • 8. Electronic Health Records•  E.g. patient transfers in the hospital•  Event types: ARRIVAL Arrive the hospital EMERGENCY Emergency room ICU Intensive Care Unit FLOOR Normal room DISCHARGE-ALIVE Leave the hospital alive DIE Leave the hospital dead
  • 9. Improve the Quality of Care! Patient ID: 45851733 Patient ID: 45851732!"#$"#"$$%&!(") &*++,-./& Emergency Department!"#$"#"$$%&!(")ID: 45851731 Patient &012+32456& !"#$"#"$$%&!(") &*++,-./& 6,000+!"#$"#"$$%&""( &789& !"#$"#"$$%&!(") &012+32456& !"#$"#"$$%&!(") &*++,-./&!"#$:#"$$%&$:($; &</==+& !"#$"#"$$%&""( &789& !"#$"#"$$%&!(") &012+32456&!"#$%#"$$%&!$($" &</==+& !"#$:#"$$%&$:($; &</==+& !"#$"#"$$%&""( &789&!"#!#"$$%&$)(!> &?,@5A.+32& !"#$%#"$$%&!$($" &</==+& !"#$:#"$$%&$:($; &</==+&& !"#!#"$$%&$)(!> &?,@5A.+32& !"#$%#"$$%&!$($" &</==+& & !"#!#"$$%&$)(!> &?,@5A.+32& patients per month &
  • 10. Visualizing event sequences
  • 11. From one event sequence...•  Single record [Cousins91], [Harrison94], [Plaisant98], … Patient ID: 45851737 !"#$"#"$$%&!(") &*++,-./& !"#$"#"$$%&!(") &012+32456& !"#$"#"$$%&""( &789& !"#$:#"$$%&$:($; &</==+& !"#$%#"$$%&!$($" &</==+& !"#!#"$$%&$)(!> &?,@5A.+32& & Time Patient #45851737 Arrival Emergency Room ICU Floor Discharge compact
  • 12. To multiple event sequences...•  Search [Fails06], [Wang08], [Vrotsou09], …
  • 13. To multiple event sequences...•  Search [Fails06], [Wang08], [Vrotsou09], …
  • 14. To multiple event sequences...•  Search [Fails06], [Wang08], [Vrotsou09], …•  Group [Phan07], [Burch08], [Wang09], … 1 { 2 {
  • 15. Summarizee.g. 1) What happened to the patients after they arrived? Arrival! ? ? 2) What happened to the patients before & after ICU? ICU! ? ? ? ?
  • 16. Overview / Summary Millions of records!
  • 17. Challenges•  Display millions of records on one screen –  Limited space (typical monitors) –  Scalability (millions of records?) –  Aggregation•  While preserve important information –  All possible sequences –  Gap between each pair of events
  • 18. LIFEFLOW Picture > 1000 wordsLifeFlow > 1000 event sequences
  • 19. LIFEFLOW… is novel… is scalable… provides the missing overview… summarizes all possible sequences and time gap between events
  • 20. VIDEO esign wDLifeFlo
  • 21. DEMO emonstration wDLifeFlo
  • 22. Case Study#1: Medical6,000+ Improve the Quality of Care!patients per month Feedback •  Big picture + anomalies •  Less worry about query formulation, more time thinking about new questions •  Long-term monitoring
  • 23. Case Study#2: Transportation200,000+ Compare traffic agencies ! traffic incidents
  • 24. 100 years!
  • 25. Clean the data.
  • 26. Video
  • 27. Case Study#2: Transportation200,000+ Compare traffic agencies ! traffic incidents Feedback •  Reveal unexpected sequences •  Identify data errors •  Can ask more questions, faster, and richer
  • 28. Other Datasetse.g. researchers’ publications (from Springer)
  • 29. 9,000+ JOURNAL (1ST) researchers JOURNAL BOOK CHAPTER (1ST) BOOK CHAPTER
  • 30. DataKitchenMake your raw data ready to eat
  • 31. Take away messages•  Life is full of event sequences.•  LifeFlow is a visual summary that supports an exploration of event sequences.•  We will be happy to try LifeFlow with your data.
  • 32. Acknowledgement•  Washington Hospital Center Phuong Ho, Mark Smith, David Roseman http://www.whcenter.org•  National Institutes of Health (NIH) Grant RC1CA147489-02 http://www.nih.gov•  Center for Integrated Transportation Systems Management (CITSM) (a Tier 1 Transportation Center at the University of Maryland) Michael Pack, Michael VanDaniker, Nikola Ivanov http://www.cattlab.umd.edu
  • 33. Take away messages•  Life is full of event sequences.•  LifeFlow is a visual summary that supports an exploration of event sequences.•  We will be happy to try LifeFlow with your data. Contact me kristw@cs.umd.edu! www.cs.umd.edu/hcil/lifeflow