Space-scale diagrams: understanding multiscale interfaces
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
DTLens: multi-user tabletop spatial data exploration
Proceedings of the 18th annual ACM symposium on User interface software and technology
Spatiotemporal reasoning about epidemiological data
Artificial Intelligence in Medicine
Shallow-depth 3d interaction: design and evaluation of one-, two- and three-touch techniques
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Flood Emergency Interaction and Visualization System
VISUAL '08 Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management
Using hands and feet to navigate and manipulate spatial data
CHI '09 Extended Abstracts on Human Factors in Computing Systems
Wireless applications for hospital epidemiology
Proceedings of the 1st ACM international workshop on Medical-grade wireless networks
PyMT: a post-WIMP multi-touch user interface toolkit
Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces
BioSurveillance'07 Proceedings of the 2nd NSF conference on Intelligence and security informatics: BioSurveillance
IICS'04 Proceedings of the 4th international conference on Innovative Internet Community Systems
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Hospital infections cost the lives of more than 100,000 people in the United States every year. Understanding how infections spread in hospitals is critical to reducing this problem. To help in this endeavor, we developed an interactive, multi-touch hospital contact-network visualization and disease spread simulation. The system visually animates healthcare workers as they move through a hospital building based on a very large, real world dataset of electronic medical record login sessions. Users control the visualization and infection spread simulation by direct manipulation using multi-touch interactions and on screen controls. Through our implementation, we explore how infection control experts might use visual analytics and multi-touch user interfaces to explore such large datasets. We share the feedback gathered from three domain experts, who tested our application and suggested additional use cases for similar systems or potential datasets.