Solutions

4D-VIZ

New classes of information systems have the ability to collect, store, share, and analyze a vast array of operational and intelligence data, creating a situation where more data are collected than can be efficiently and effectively used in support of intelligence tasks.  At the same time, online open sources and emerging social media (e.g., blogs, open commentary on newspaper sites, tweets) offer a near real-time window into situations as they occur on the ground as well as the public sentiment evolving around those situations.  These types of sources, however, yield an even more massive quantity of content that is almost exclusively textual and unstructured in nature.  In all cases, the common problem lies in the fact that within the enormous amount of heterogeneous data there exist elements and patterns which, if they can be discovered and understood, are critical to collaborative sensemaking across an ever broader and more disparate community of intelligence analysts and consumers.

 

CHI Systems has developed a web-based modular platform, 4D-Viz, to support this process.  4D-Viz is an integrated tool suite which supports modular analysis and collaboration through data acquisition, data mining, analysis, visualization, reporting, and alerting capabilities.  4D-Viz supports geospatial, temporal, network, textual, and sentiment analyses through a combination of search-based, visual analytic, and automated analysis technologies.  4D-Viz’s design is centered around the intelligence analyst, allowing for the creation, inspection, and correlation of data entities (e.g., persons, places, events), using a search-driven paradigm and supporting a tight integration of multiple coordinated views.  To facilitate data exploration, 4D-Viz supports data visualization techniques such as: geospatially mapping locations (both static and dynamic), displaying occurrences over a timeline, depicting relationships (e.g., social) through network graph displays, and illustrating connections between elements which are separately contextualized in geographic and network space.