The analysis of information is an area of growing importance. With increasing computational capacity, extremely large, heterogeneous data sets are becoming commonplace. However, techniques for analyzing such data lag far behind the ability to produce it. Information analysis is a broad term that includes the integration and management of information, as well as the techniques for extracting from massive quantities of data various types of important, anomalous, interesting, or unexpected phenomena. Raw data sets come from diverse sources and in various forms.
Some information is stored in databases, other information is collected and available in real-time.
Some of the raw data may be noisy, erroneous, or incomplete. The process of acquiring and creating large quantities of data has become highly automated, however the process of assimilating and analyzing the data has not. We are concerned with developing advanced information analysis techniques to exploit existing data to enhance the understanding and interpretation of complex, large-scale, heterogeneous systems. The scientific, manufacturing, economic, military, and medical communities increasingly rely on modeling and simulation technologies to harness the growing complexity of the systems and environment in which they operate. Climate and ocean modeling, forecasting of the spread of infectious diseases, and modeling of traffic patterns are some of the applications undertaken at the Laboratory.