| dc.description.abstract | To fight terrorism successfully, the quality of data must be considered to avoid
garbage-in-garbage-out. Research has shown that data quality (DQ) goes beyond
accuracy to include dimensions such as believability, timeliness, and accessibility. In
collecting, processing, and analyzing a much broader array of data than we do
currently, therefore, a comprehensive approach must be developed to ensure that DQ
is incorporated in determining the most probable current or future scenario for
preemption, national security warning and decision making. Additional data such as
who was the data source, when was the data made available, how, where, and why
also need to be included to judge the quality of the information assembled from these
data.
We propose such an approach for Total Information Awareness with Quality (TIAQ),
which includes concepts, models, and tools. Central to our approach is to manage
information as a product with four principles. We have applied the information product
approach to research sites where opportunities arise. For example, the Air Force
Material Command uses requirements definition and forecasting processes to perform
a number of functions. However, the Air Force experienced several complex problems
due to DQ problems; as a result, fuel pumps were unavailable. Each engine needs a
fuel pump; when a pump is not available, a military aircraft is grounded. We traced the
fuel-pump throughout the process of remanufacture, and identified root causes such as
delays by pump contractors and ordering problems. To a certain extent, detecting
foreign terrorists and decipher their plots are analogous to tracing fuel pumps. Our
research provides an interdisciplinary approach to facilitating Total Information
Awareness | en |
