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Surface mail address: 2117C Hornbake South Wing, 4130 Campus Dr. University of Maryland, College Park, MD 20742, U.S.A.
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Inspired EHRs: Designing for Clinicians (2014)
Journal Special Issues
State of the Field and New Research Directions, Information Visualization, 10(4), 2011. Guest Editors: Catherine Plaisant, Andreas Kerren, Stasko
Evaluation of Visual Analytics, IEEE Computer Graphics and Applications (May/June 2009).
Special Issue in Honor of Ben Shneiderman’s 60th Birthday: Reflections on Human-Computer Interaction,
Editor of the HCIL Video Report Series (1991-2006).
Some (including the 2000 retrospective) are also available in the Open Video Project (a pioneer of video digital libraries).
Later videos are included in the project pages.
|Catherine Plaisant is a Research Scientist Emerita at the University of Maryland Institute for Advanced Computer Studies and a member of the Human-Computer Interaction Lab (HCIL). Catherine earned a Doctorat d’Ingénieur degree in France (similar to an Industrial Engineering PhD) and joined HCIL in 1988. She works with multidisciplinary teams on designing and evaluating new interface technologies that are useful and usable. In 2015 she was elected to the ACM SIGCHI Academy recognizing principal leaders in the field of Human-Computer Interaction. In 2018 she was awarded an INRIA International Chair, and in 2020 she received the IEEE VIS Career Award and the ACM SIGCHI Lifetime Service Award.
Catherine Plaisant has published over 200 papers, on subjects as diverse as information visualization, medical informatics, universal access, decision making, digital humanities or technology for families. Her work spans the interface development lifecycle, with contributions to requirements gathering, interface design, and evaluation.
With long term collaborator Ben Shneiderman she co-authored the 4th, 5th and 6th Editions of Designing the User Interface, one of the major books on Human-Computer Interaction.
This technique helps users create meaningful clusters in social networks. Users compare results of all available clustering algorithms in a mixed-initiative approach, and see how they match prior knowledge. This is a joint project with the INRIA AVIZ lab.
From 1983 to 2002 the CHI Conference published a yearly Technical Video Program distributed on VHS videotapes. We are now working to preserve those video demonstrations and archive them in the ACM Digital Library.
PAOHVIS: Dynamic Hypergraphs Visualization
Visualization of transportation data: I helped the Center for Advanced Transportation Technology design or redesign the user interface of products for transportation managers and analysts. See RITIS (and also this much older HCIL transportation project)
PeerFinder explores the challenge of finding people like you, i.e. finding records similar to a seed record, based on record attributes AND event history. We know that users do not trust the advice of blackbox algorithms for important decision making, and we believe that transparency and user control can increase trust in recommendations that are based on people similarities.
EventAction introduces prescriptive analytics for temporal event sequences. The idea is to help users make plans based on data from similar people who achieve the desired outcome.
CoCo (short for COhort COmparison) helps analysts compare two groups of records such as patients records or student records to find differences in the event sequences found in the groups.
EventFlow for event analytics is now used by many researchers. EventFlow allows them to 1) search for specific patterns of events 2) see an overview of all sequences and 3) simplify the data to reveal useful patterns.
Twinlist: explored how visual layout and animation can help clinicians see similarities in drug lists and rapidly make decisions about which drugs to keep and which one to discontinue.
Related project: SHARP-C: Novel user interfaces for clinicians
Treeversity visualizes changes over time of dynamic hierarchical data. Users can analyze relative and absolute change over a variable in each node, as well as created and removed nodes. They can also compare non inherently hierarchical datasets, by grouping them by attributes.
ManyNets: Looking at multiple networks or communities at once.
Visual Analytics Evaluation : The SEMVAST project helped develop benchmarks datasets and metrics for evaluation. I co-chaired the 1st IEEE Visual Analytics Challenge for several years starting with the 1st Challenge in 2006, and maintain the Visual Analytics Benchmark Repository.
iSonic : making georeferenced data accessible to users with visual impairments
Dynamic Queries, and Query Preview (an ancestor of faceted search)
LifeLines for Visualizing Medical Patient Records (and other personal histories)
Touchscreen Toggles (ON/OFF selection)
Trees and hierarchies
June 4, 2021
Oct. 27, 2020
Feb. 9, 2020
Sept. 1, 2019