Many visual analysis tools operate on a fixed set of data. In some cases, a fixed set of data is appropriate.  However, professional analysts follow issues over a period of time and need to be able to  easily add new documents to an ongoing exploration. Some analysts must handle documents in a new window of time, with new documents constantly added and old ones aging out. This work focuses on supporting the visual discourse of an analyst using a dynamic moving window of documents, calculated incrementally.

Researchers at PNNL have developed a system designed to support analysis of constantly evolving text collections. The data visualization system includes accessing an  initial set of documents at a first moment in time and generates a first visualization depicting associations.  At a second moment in time a second set of documents is added to the system and a second visualization is generated.  Over time old documents may be aged off as new documents arrive. The system supports the ability to monitor the visualization and see what’s new each time a new increment of data is processed and loaded into the system while minimizing the disruption to both the analytic process flow and the interaction flow.

The PNNL-developed visual analysis system supports complex cognitive work and the continuous development of understanding and judgments about the available data. Moving from analysis of static collections to dynamic analysis of changing collections of data has opened important new applications and insights for analysts.