EventFlow: Visual Analysis of Temporal Event Sequences
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- Join us on May 26, 2016 for the HCIL Annual Symposium in College Park. We will have a workshop on Temporal Event Sequence Analysis + EventFlow and Coco User Group Meeting.
- See also the project that came after Eventflow: CoCo for Cohort Comparison.
- A summary of analysts’ strategies using EventFlow: Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus.
- EventFlow is now available for Commercial Licensing (see below).
- Oracle produced a nice video highlighting our work.: January 2013.
EventFlow is a novel tool for event sequence analytics. It includes a timeline display showing all individual records and their point and interval events, as well as a aggregated view of all the sequences in the dataset. Multiple graphical search capabilities enable users to find records that exhibit specific temporal patterns. Interactive features allow users to review patterns, find anomalies or construct cohorts, but also allow them to simplify the data in order to sharpen the analytic focus and answer questions about the data.
Eventflow has been used in a variety of application domains: medical research, log analysis, cybersecurity, sports analytics, incident management etc. The analysis of healthcare data has been our main focus in term of number of partners.
Medical researchers and hospitals have applied EventFlow to analyze treatment patterns and outcomes in Electronic Health Records or claims reports, while network security analysts have studied cyberattack patters and sports analysts have found novel approaches to studying games, overall team performance, and seasonal patterns. Education researchers and universities have used EventFlow to look at class enrollment sequences and student records. Applications for web log, sensor data, business processes, and financial transactions are also emerging markets.
If you are interested in how EventFlow is being used we have listed a few case study reports below (in the Publications section), or join us during the HCIL Annual Symposium.
The HCIL’s ongoing work with temporal event records has produced powerful tools for analyzing and exploring patterns of point-based events (Lifelines2, LifeFlow). However, users found that point-based events limited their capacity to solve problems that had inherently interval attributes, for example, the 3-month interval during which patients took a medication. To address this issue, EventFlow extends its predecessors to support both point-based and interval-based events. Interval-based events represent a fundamental increase in complexity at every level of the application, from the input and data structure to the eventual questions that a user might ask of the data. Our goal was to accomplish this integration in a way that appeared to users as a simple and intuitive extension of the original LifeFlow tool. With EventFlow, we present novel solutions for displaying interval events, simplifying their visual impact, and incorporating them into meaningful queries.
- Sana Malik, PhD Candidate, Computer Science
- Fan Du, PhD Candidate, Computer Science
- Catherine Plaisant, Research Scientist, UMIACS
- Ben Shneiderman, Professor, Computer Science
- Megan Monroe, PhD Candidate, Computer Science
- Christopher Imbriano , PhD Candidate, Computer Science
- Rongjian Lan, PhD Candidate, Computer Science
- Krist Wongsuphasawat PhD, Computer Science
We appreciate the collaboration of clinical researchers and epidemiologists at the US Army Pharmacovigilance Center, University of Maryland School of Pharmacy, National Children Hospital, University of Florida, Washington Hospital Center, and many others.
We appreciate the partial support of Oracle Corporation and Adobe Corporation. Past funding was provided by the Center for Health-related Informatics and Bioimaging (CHIB) at the University of Maryland. EventFlow also builds on early work which was funded in part by NIH – National Cancer Institute grant RC1-CA147489 “Interactive Exploration of Temporal Patterns in Electronic Health Records” (for LifeLines2 and LifeFlow), and later by the Maryland Industrial Partnerships (MIPS) program and Pulse8.
|If you are in a rush, this video provides a good overview of how the EventFlow aggregation is constructed, and how the search and replace can be used to manipulate the data to answer questions||Or: take a look at the analysis of BASKETBALL data: Basketball Play-by-play Analysis
|The Offensive Rebounding of the Indiana Pacers
|Or see an older demo but still useful because it stats with a different example dataset (exploring patient paths after they enter the Emergency Room – e.g. looking for bounce back)
Download & Licensing
We can provide you with a review version of Eventflow:
- For non-commercial use: please contact firstname.lastname@example.org with a description of your project and organization.
- For commercial use: EventFlow is available for licensing. To request a review copy of EventFlow and for more information about licensing please contact:
Office of Technology Commercialization (OTC)
2130 Mitchell Building, University of Maryland, College Park, MD 20742
Phone: 301-405-3947 | Fax: 301-314-9502
- Not sure: contact email@example.com
- Users can watch the videos above, or refer to the EventFlow Manual, which covers all the major features of EventFLow and includes a large number of detailed videos.
- To learn more about the EventFlow data format, go to the EventFlow data format section in the user manual.
- To generate datasets for testing, use the Dataset Generator.
- Suggestions for dealing with large datasets: Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus.
- Users can also participate in our workshops (example from 2015) and EventFlow User Group Meeting to share their experiences using EventFlow, and ideas for potential improvements.
[BEST REFERENCE] Simplification of temporal event sequences:
Megan Monroe, Rongjian Lan, Catherine Plaisant, Ben Shneiderman
Temporal Event Sequence Simplification
TVCG: IEEE Transactions on Visualization and Computer Graphic, 2013.
The EventFlow graphical query interface:
Megan Monroe, Rongjian Lan, Juan Morales del Olmo, Catherine Plaisant, Ben Shneiderman, Jeff Millstein
The Challenges of Specifying Intervals and Absences in Temporal Queries: A Graphical Language Approach.
CHI: In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2013.
Strategies used by analysts:
Fan Du, Ben Shneiderman, Catherine Plaisant, Sana Malik, Adam Perer
Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus
TVCG: IEEE Transactions on Visualization and Computer Graphic, 2016 (in press).
Technical paper on temporal query processing algorithms
Megan Monroe, Amol Deshpande
An Integer Programming Approach to Temporal Pattern Matching Queries
SSTDM: In Proceedings of International Workshop on Spatial and Spatiotemporal Data Mining, 2013.
A case study of our collaboration effort with the US Army Pharmacovigilance Center:
Megan Monroe, Tamra Meyer, Catherine Plaisant, Rongjian Lan, Krist Wongsuphasawat, Trinka Coster, Sigfried Gold, Jeff Millstein, Ben Shneiderman.
A Pilot Study of Asthma Medications in the Military Health System.
VAHC: In Proceedings of Workshop on Visual Analytics in HealthCare, 2013.
A detailed version of the above US Army case study (part of Book Chapter)
Catherine Plaisant, Megan Monroe, Tamra Meyer, Ben Shneiderman
Book Chapter in Big Data and Health Analytics, Marconi, K. and Lehman, H. (Eds), CRC Press – Taylor and Francis, pp 243-262, 2014.
Carter, E., Burd, R., Monroe, M., Plaisant, C., Shneiderman, B.
Using EventFlow to Analyze Task Performance During Trauma Resuscitation
In Proceedings of the Workshop on Interactive Systems in Healthcare (WISH), 2013.
Prescriptions adherence analysis
Bjarnadottir, M., Malik, S., Onukwugha, E., Gooden, T., Plaisant, C. (October 2015)
Understanding Adherence and Prescription Patterns Using Large Scale Claims Data
PharmacoEconomics, Volume 34, Issue 2, pp 169-179, 2016.
Health service utilization among cancer patients (part of Book Chapter)
Onukwugha, E., Plaisant, C., Shneiderman, B. (October 2015)
Data Visualization Tools for Investigating Health Services Utilization Among Cancer Patients
Book chapter in Hesse, B., Ahern, D., and Beckjord, E. (Eds.) Oncology Informatics, Elsevier, 2016 (to appear).
Workflow for pediatric asthma patients
Mustafa Ozkaynak, Oliwier Dziadkowiec, Rakesh Mistry, Tiffany Callahan, Ze He, Sara Deakyne, Eric Tham
Characterizing Workflow for Pediatric Asthma Patients in Emergency Departments Using Electronic Health Records
Journal of Biomedical Informatics, Volume 57, pp 386-398, 2015.
Short Papers and Technical Reports
Late-breaking work on temporal event sequence overview simplification
Matthew Louis Mauriello, Ben Shneiderman, Fan Du, Sana Malik, and Catherine Plaisant
Simplifying Overviews of Temporal Event Sequences (Best Paper Honorable Mention)
Early work on temporal event sequence search and replace
Rongjian Lan, Hanseung Lee, Megan Monroe, Allan Fong, Catherine Plaisant, Ben Shneiderman
Temporal Search and Replace: An Interactive Tool for the Analysis of Temporal Event Sequences
Early report on extending the Lifeflow overview visualization to handle interval data
Megan Monroe, Krist Wongsuphasawat, Catherine Plaisant, Ben Shneiderman, Jeff Millstein and Sigfried Gold
Exploring Point and Interval Event Patterns: Display Methods and Interactive Visual Query
Other publications written by our case study partners
E. Onukwugha, Y. Kwok, C. Yong, C. Mullins, B. Seal, A. Hussain
Variation in the length of radiation therapy among men diagnosed with Incident Metastatic Prostate Cancer”
ASTRO: Poster presented at the 2013 American Society for Radiation Oncology meeting.
* See also related HCIL Workshops below, as they included presentations from EventFlow users.
General survey paper
Rind, A., Wang, T., Aigner, W., Miksch, S., Wongsuphasawat, K., Plaisant, C., Shneiderman, B.
Interactive Information Visualization for Exploring and Querying Electronic Health Records: A Systematic Review
Foundations and Trends in Human-Computer Interaction, Vol. 5, No. 3, 207-298, 2013.
Hunter Whitney, It’s About Time, UX Magazine, September 2014.
Products and papers stimulated by this work
Our original research on LifeFlow and EventFlow stimulated new work by other labs, such as:
- OutFlow and CareFlow at IBM.
- Visualizing Uncertain Critical Paths in Schedule Management, by Robert Gove, Brandon Herzog (see VAST 2013 Industry posters).
Related projects and events
- 2015 HCIL Workshop on Visualization of Temporal Patterns in EHR data:, in association with the Annual HCIL Symposium, May 28, 2015, College Park.
- Links of all HCIL Projects related to Temporal Visualization: LifeLines, LifeLines2, PatternFinder, LifeFlow, etc.
- (several years) Visual Analytics in Healthcare workshops at AMIA or IEEE Vis, with for example Ben Shneiderman’s keynote and 2 papers and demos in 2013.
- 2014 IEEE VIS Workshop on Visualization of EHR data, Paris, France, November 9, 2014.
- 2014 HCIL Workshop on Visualization of Temporal Patterns in EHR data:, in association with the Annual HCIL Symposium, May 29, 2014, College Park.
- 2013 HCIL EHR Informatics Workshop
- 2012 EventFlow User Group Meeting
- 2012 HCIL EHR Informatics Workshop 2012
- 2011 HCIL EHR Informatics Workshop
- 2008 HCIL Interactive Visual Exploration of Electronic Health Records
- 2004 HCIL Personal Medical Devices Workshop: Increasing Patient Healthcare Participation
- 1997 HCIL Visualizing Personal Histories Workshop
Presentations (list non updated)
The following slides provide an introduction to the motivation behind EventFlow, and a summary of its features.
A full description can be found in the tech report.
- Temporal Event Querying – Presented at CHI2013
- Dataset Simplification – Presented at MedStar 2/13
- Basketball Play-by-play Analysis – Presented at the 2013 HCIL Symposium