Our user experience effort focuses on the development and assessment of prototype decision support systems that help integrate our R&D in technology and tradecraft. Our goal is to develop front-end user experiences that allow analysts to leverage appropriate back-end analytic techniques and technology by making them available as modular components in a service-oriented computing architecture.
The user experience is where Anticipatory Intelligence tradecraft meets predictive analytics. We target our work in analytics to focus on question and hypothesis generation and management, data triage and exploration, data visualization, selecting measurably relevant information, assessing data veracity, and developing predictions across a range of scenarios and data representations. Our goal is to provide technology, tradecraft, and tools that can swiftly and collaboratively be repurposed as new challenges emerge: detecting and modeling the members of a new social movement and their behaviors, understanding the emergence of a new technology, or understanding the behavior of competitors/adversaries in a business or analytic sector.
Some of the key enabling areas of research and application include:
- Recommender systems
- Visual analytics for data exploration and triage
- Feature extraction and anomaly detection in large, multimodal data
- Automated and semi-automated hypothesis generation
- Metrics for data veracity, relevance, and utility
- Question decomposition and evidence mapping
- Prediction and uncertainty quantification