Natural Language Processing and Prioritization for Contextual Symbolic Rendering

With the desire to be prepared for possible threat scenarios, DHS has access to data, but it can be disparate with a mix of structured and unstructured data in very large quantities. Information from a variety of sources needs to be ingested and processed in order to determine the "what, when, where, and how bad", then presented geospatially for monitoring and analysis purposes. Constructing and maintaining a single representation of an incident ("object") which is updated over time as the details of the situation change is essential, along with the ability to prioritize the incidents being displayed to focus attention. To address these challenges, Digital Sandbox will conduct research and demonstrate software prototypes focused on the analysis, prioritization, and presentation of contextual symbolic information. The resulting capability will improve operational situational awareness at a fraction of the cost and time possible with existing technology and approaches, especially for organizations tasked with public safety operations and intelligence analysis.