An IEEE VIS 2016 Workshop

The Event Event:
Temporal & Sequential Event Analysis

October 24, 2016. Baltimore, Maryland.

Schedule of Events. Monday, October 24, 2016

2:00-2:10pm Welcome from Chairs
2:10-2:25pm Introductory Session with Ben Shneiderman
2:25-3:15pm Paper Session #1: Directions and Challenges
3:15-4:00pm Paper Session #2: Advanced Techniques
4:00-4:15pm Coffee Break
4:15-4:55 Paper Session #3: Systems / Applications
4:55-5:45 Poster/Demo Session
5:45-5:55 Wrap up with Co-Chairs

Important Dates

Papers August 26, 2016 (Extended)
Notifications September 8, 2016
Workshop October 24, 2016

Call For Papers

As visualization researchers, our ongoing challenge is often to leverage the voluminous data that is being captured to drive decision making and insights. Common to such data are temporal events, data points with both a timestamp and event type, so understanding patterns of temporal event sequences is an important problem to many domains.

For example, medical researchers may wish to leverage the data captured by electronic health records to determine if certain sequences of medical events correlate with positive outcomes. Similarly, city government officials may wish to leverage the temporal data collected from their transportation systems, call centers, and law enforcement agencies to improve their cities’ services. Engineers might analyze temporal events from system logs to manage large-scale distributed system performance. Consumer services analysts might seek to understand social media and shopping patterns.

Recently, there has been an increasing amount of visualization research focusing on temporal events. Papers on this topic have appeared at IEEE VIS, other visualization conferences, and at many domain-specific venues.

The main question behind the proposed workshop is: How can we unify and advance the role of visualization in temporal event analysis? The workshop will gather visualization researchers together to discuss the interesting opportunities and challenges visualization may face with temporal events. It aims to both gather the existing literature on the subject and build a research agenda for future research.

In order to encourage collaboration and comparison, we will distribute 1-2 sample datasets before the workshop. We will encourage, but not require, presenters of papers and demos to show how their system performs on these sample datasets; this will better allow us all to discuss the tradeoffs of different designs.

Topics and Scope

This workshop aims to increase awareness about this interesting opportunity for visualization research, collect and compare examples of existing and ongoing research in this area, and to create a preliminary temporal event analytics research agenda for visualization researchers. The workshop will allow participants to showcase their existing research and ideas, and to learn and reflect on the latest advances in visualization of temporal events. Therefore, work which addresses any of the following questions would be highly relevant:

  • How can visualization help data scientists make sense of temporal events?
  • How can end users be sure the visualizations are made of temporal-relevant features?
  • How can visual analytics help researchers include their domain knowledge into the temporal event analysis process?
  • How do we build benchmark datasets and ground truth to objectively compare different temporal event visualizations?
  • What are good and suitable processes to ensure usefulness of event visualizations?
  • How can we use visual analytics to “explain” patterns derived from frequent sequence data mining algorithms?
  • How can visualization help sequence visualizers gain trust into their results?
  • How can we compare and evaluate extant methods for temporal event analysis?
  • What techniques are good for what situations (many different event types vs. few event types; many users vs. few users; long streams vs. short streams?)
  • Can we gather some sample datasets to help compare and contrast existing techniques>
Research topics include, but are not limited to, the following:
  • Visualization techniques for temporal event analysis,
  • Real and synthetic data sets and benchmarks,
  • Taxonomies of temporal event analysis tasks,
  • Case studies, user Challenges, and user Stories of temporal event visualizations.
  • Theory and algorithms for event analysis (e.g., data structures, models, taxonomies, etc.)

How to Submit

We solicit a wide range of submissions which fall within the scope outlined above. Authors are invited to submit to any of three tracks:
  • Research papers (3-4 pages) should present new work or a novel synthesis of already published research contributions. Articles describing emerging research or works-in-progress are welcome. Submissions will be peer-reviewed by the organizers and accepted manuscripts will be made available on the workshop website. Authors of accepted papers will have the opportunity to orally present their work during the workshop.
  • Position papers (1-2 pages) are short statements describing ideas to discuss during the workshop. They will be peer-reviewed by the organizers, and accepted papers will be made available on the workshop website.
  • Poster or Interactive Demonstration abstracts (1-2 pages). Submissions will be peer-reviewed by the organizers, and accepted abstracts will be made available on the workshop website. Authors of accepted papers will have the opportunity to showcase their work during a poster/demo session at the workshop.
Submissions are open and due by August 22, 2016. Papers should be formatted using the TVCG Formatting Guidelines and submitted as a PDF.

Replace the default copyright block found in the TVCG template with:

Proceedings of the IEEE VIS 2016 Workshop on Temporal & Sequential Event Analysis.
Available online at:

Please submit your papers using EasyChair at

During the submission process, you will be asked to select the appropriate track (Research Papers or Position Papers or Posters).


Please feel free to engage with the workshop organizers and participants here before the conference.

Sample Datasets

One of the goals of this workshop is to curate a collection of temporal and sequential datasets to make them widely available to researchers working in this domain. The following datasets are an initial collection of datasets we hope to expand as an output of this workshop.
Aguvue (Full)Application event log dataPoints
Aguvue (Sample)Application event log dataPoints
ACT Testing DataIEEE VGTC VPG International Data-Visualization Contest of ACT Testing CentersPoints
Hospital TransfersContains the (synthetic but realistic) series of departments that patient get transferred through during their stay in the hospital.Points
ProfessorsContains the series of appointments, conferences, and publications that academic professionals go through as they attain full-time professor status.Points and Intervals
Chicago Bulls SeasonContains the entire 2012-2013 Chicago Bulls season, including an Offense → Defense dataset, a Defense → Offense dataset, and a config file that can be loaded with either.Points and Intervals
UMD vs. UNCContains Maryland's 2012-2013 game against UNC, including an Offense → Defense dataset, a Defense → Offense dataset, and a config file that can be loaded with either.Points and Intervals


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Adam Perer

Adam Perer s a research scientist at IBM T.J. Watson Research Center. His recent research focuses on visualization and analytic techniques for making sense of electronic medical records and social networks. Increasingly, he has been working on developing new techniques for visualizing frequent event sequences in temporal data. He received his Ph.D. in Computer Science from the University of Maryland.

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Steven Drucker

Steven Drucker is a Principal Researcher at Microsoft Research. His recent research focuses on techniques for natural exploration and presentation of data. He has been looking at ways of democratizing visualization systems including touch interaction; facilitating designer interaction, and temporal sequence analysis.

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Danyel Fisher

Danyel Fisher is a Senior Researcher at Microsoft Research. His recent research focuses on big data analytics and exploratory visualization; on designer interaction, and on temporal sequence analysis. With Miriah Meyer, he is a co-author of “Making Sense of Data, to be published by O’Reilly in 2016.

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David Gotz

David Gotz is Associate Professor of Information Science at the University of North Carolina at Chapel Hill (UNC-Chapel Hill) and Associate Director for the Carolina Health Informatics Program. His recent research focuses on visual analytics and communication methods for helping domain experts discover insights and take action based on large collections of temporal event data. He received his Ph.D. in Computer Science from UNC-Chapel Hill and was previously a Research Scientist at the IBM T.J. Watson Research Center.

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Megan Monroe

Megan Monroe is a research scientist at IBM’s Cognitive User Experience lab in Cambridge, MA. She received her Ph.D. in Computer Science from the University of Maryland, focusing on the visual analysis of temporal event sequences. She has worked with temporal datasets ranging from electronic health records to process logs to sports analytics.


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Catherine Plaisant

Catherine Plaisant is a Senior Research Scientist at the University of Maryland Institute for Advanced Computer Studies and Associate Director of Research of the Human-Computer Interaction Lab. Catherine Plaisant earned a Doctorat d’Ingenieur degree in France (similar to a Industrial Engineering PhD). Her research includes LifeLines and EventFlow for the analysis of temporal records.

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Ben Shneiderman

Ben Shneiderman is a Distinguished University Professor at the University of Maryland Department of Computer Science and Founding Director (1983-2000) of the Human-Computer Interaction Lab. He is a member of the National Academy of Engineering and recipient of the IEEE TVCG Career Achievement Award. His work on temporal event data is largely with EventFlow.