Context-Aware Computing Rediscovers Information for Intelligence Analysts


Analysts review and file hundreds of pieces of data from multiple sources amid the everyday challenges of interagency sharing requirements and compressed timetables to provide mission-critical intelligence. However, mission success may depend on analysts re-finding that same, now critical bit of data weeks or months after they first discovered it. But making rediscovery even more difficult is how analysts organize their data

Analysts traditionally file data in highly personalized ways, meaning that filing methods across the intelligence enterprise can be quite diverse. As a result, personalization may make it more difficult for analysts to share data files and rediscover the original context of the data.

According to Mark Hoffman, Advanced Technology Laboratories (ATL) technology manager at Lockheed Martin, a new application called Contrail, developed at Lockheed Martin captures the analysts’ trails of discovery and reasoning as well as the items they encountered along the way, helping analysts to ‘rediscover’ stored information, find and share new information, and provide an audit trail for items like capturing lessons learned.

Integrated into an intelligence agency’s computing infrastructure, Contrail’s software builds an explicit, machine-understandable representation of analysts’ contexts by monitoring how they handle information. The technology then builds a personalized software model that automatically tags newly found data, enabling analysts to later retrieve that needed intelligence using metadata, content, or context at time of storage.

Analysts can also share data by using context tags – such as people, places, events, or concepts active when they first stored the data. During searches, Contrail automatically suggests stored items that are relevant by matching the current situational context with that on the tags of stored items.

Contrail was developed in 2007 as a context-aware computing framework that gives the intelligence community the tools to capture, retrieve and share contextually relevant information at reduced time and cost. It was developed as part of the Collaboration and Analyst/System Effectiveness program sponsored by the Intelligence Advanced Research Projects Activity. Through internal research and development, ATL continues to expand Contrail’s functionality.