In time-sensitive environments, such as DHS emergency operations centers (EOCs), it is imperative for decision makers
to rapidly understand and address key logical relationships that exist between tasks, entities, and events, even as
conditions fluctuate. These relationships often have important temporal characteristics, such as tasks that must be
completed before others can be started (e.g., buses must be transported to an area before an evacuation process can
begin). Unfortunately, traditional temporal display methods, such as mission timelines, typically reveal only rudimentary
event details and fail to support user understanding of and reasoning about critical temporal constraints and
interrelationships across multiple mission components. To address these shortcomings, we developed a visual language
to enhance temporal data displays by explicitly and intuitively conveying these constraints and relationships to decision
makers. In this paper, we detail these design strategies and describe ongoing evaluation efforts to assess their usability
and effectiveness to support decision-making tasks in complex, time-sensitive environments. We present a case study in
which we applied our visual enhancements to a timeline display, improving the perception of logical relationships
among events in a Master Scenario Event List (MSEL). These methods reduce the cognitive workload of decision
makers and improve the efficacy of identification.
With the increase of terrorist activity around the world, it has become more important than ever to analyze and
understand these activities over time. Although the data on terrorist activities are detailed and relevant, the complexity of
the data has rendered the understanding and analysis difficult. We present a visual analytical approach to effectively
identify related entities such as terrorist groups, events, locations, etc. based on a 2D layout. Our methods are based on
sequence comparison from bioinformatics, modified to incorporate the element of time. By allowing the user the
freedom to link entities by their activities over time, we provide a new framework for comparison of event sequences.
Our scoring mechanism is robust and flexible, giving the user the flexibility to define the extent to which time is
considered in aligning entities. Incorporated with high interactivity, the user can efficiently navigate through tens of
thousands of records recorded in over a hundred dimensions of data by choosing combinations of categories to examine.
Exploration of the terrorist activities in our system reveals relationships between entities that are not easily detectable
using traditional methods.