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FINDING PATTERNS IN TEMPORAL DATA KRIST WONGSUPHASAWAT JOHN ALEXIS - PowerPoint PPT Presentation

FINDING PATTERNS IN TEMPORAL DATA KRIST WONGSUPHASAWAT JOHN ALEXIS GUERRA GMEZ TAOWEI DAVID WANG CATHERINE PLAISANT BEN SHNEIDERMAN HUMAN-COMPUTER INTERACTION LAB UNIVERSITY OF MARYLAND FINDING PATTERNS IN TEMPORAL DATA KRIST


  1. FINDING PATTERNS IN TEMPORAL DATA KRIST WONGSUPHASAWAT JOHN ALEXIS GUERRA GÓMEZ TAOWEI DAVID WANG CATHERINE PLAISANT BEN SHNEIDERMAN HUMAN-COMPUTER INTERACTION LAB UNIVERSITY OF MARYLAND

  2. FINDING PATTERNS IN TEMPORAL DATA KRIST WONGSUPHASAWAT JOHN ALEXIS GUERRA GÓMEZ TAOWEI DAVID WANG CATHERINE PLAISANT BEN SHNEIDERMAN HUMAN-COMPUTER INTERACTION LAB UNIVERSITY OF MARYLAND

  3. NEW STUFF Needs for an overview -> LifeFlow!

  4. TASKS • Example: Finding “Bounce backs” ICU Floor ICU within days • Other questions Arrival ICU

  5. LIFEFLOW VISUALIZE Display the aggregation RECORD RECORD RECORD AGGREGATE Merge multiple records into tree

  6. AGGREGATE • Aggregate by prefix #1 #2 #3 #4 Example with records

  7. AGGREGATE • Aggregate by prefix #1 #2 #3 #4

  8. VISUALIZE • Inspired by the Icicle tree [Fekete Number of files

  9. VISUALIZE (2) • Use horizontal axis to represent time • Video

  10. DEMO – LIFEFLOW When the lines are combined into flow

  11. FUTURE WORK • Comparison ICU Intermediate ICU Intermediate Jan-Mar April-June Floor

  12. TAKE-AWAY MESSAGE Information visualization is a powerful way to explore temporal patterns. You can work with us on new case studies.

  13. 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.

  14. EXAMPLE – TRAFFIC INCIDENTS

  15. ACKNOWLEDGEMENT D R . P HUONG H O , D R . M ARK S MITH , D AVID R OSEMAN W ASHINGTON H OSPITAL C ENTER http://www.whcenter.org N ATIONAL I NSTITUTES OF H EALTH (NIH) - G RANT CA147489 http://www.nih.gov M ICHAEL P ACK , M ICHAEL V AN D ANIKER C ENTER FOR A DVANCED T RANPORTATION T ECHNOLOGY L AB (CATT L AB http://www.cattlab.umd.edu

  16. TAKE-AWAY MESSAGE Information visualization is a powerful way to explore temporal patterns. You can work with us on new case studies. {kristw, jguerrag, tw , plaisant, ben}@cs.umd.edu http://www.cs.umd.edu/hcil/temporalviz

  17. Q&A Questions? {kristw, tw , jguerrag, plaisant, ben}@cs.umd.edu http://www.cs.umd.edu/hcil/temporalviz

  18. THANK YOU Thank you

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