Context-Aware Systems for Complex Data Analysis.

Increasingly there is a need to analyze a large quantity of diverse, multidimensional data in a timely, efficient manner. A computational awareness of context can improve the speed and accuracy of complex data analysis, and promote more effective human-machine collaboration. We describe ongoing work to develop a framework that monitors human-machine interactions, analyzes context, and augments the system (such as prioritizing information, providing recommendations, adapting an interface, adjusting the level of automation, proactively fetching data, managing notifications, sharing context with others, personalizing the system, etc.). We believe that we can facilitate complex data analysis by adapting systems to meet analysts needs based upon the varying demands of the tasks, priorities, resources, time, user state, and environment.