Sensemaking

Sensemaking is the collection and organization of information for deeper understanding to facilitate insight and subsequent action. The LAS focus in sensemaking is at the intersection of analytic tradecraft and information technology. Examples include studying decision making in volatile, uncertain, complex, and ambiguous environments; “living” reports that automatically provide differing levels of detail to different audiences; methods for developing understanding of low-level event data or large corpuses of unstructured text; automation of hypothesize-test-evaluate discovery cycle; goal and intent recognition; automatic generation of multi-media narratives.

Narrative for Sensemarking Research Project

Over the course of the LAS sponsored Narrative for Sensemaking research project, PhD students in Computer Science professor Dr. Michael Young’s Liquid Narrative Group have designed and developed an automatic narrative generation architecture and user experience that allows for the creation and rendering of multimedia narratives from underlying structured data. This system, called Bardic, is built upon the interdisciplinary approaches of Narratology, Artificial Intelligence, Computer Science and Cognitive Psychology, amongst others, and uses the concept of narrative to serve as the interlingua to bridge the chasm between data and sensemaking.

Over the course of the LAS sponsored Narrative for Sensemaking research project, PhD students in Computer Science professor Dr. Michael Young’s Liquid Narrative Group have designed and developed an automatic narrative generation architecture and user experience that allows for the creation and rendering of multimedia narratives from underlying structured data. This system, called Bardic, is built upon the interdisciplinary approaches of Narratology, Artificial Intelligence, Computer Science and Cognitive Psychology, amongst others, and uses the concept of narrative to serve as the interlingua to bridge the chasm between data and sensemaking.

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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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