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"A picture is worth a thousand words."

More of the brain is devoted to visual processing than to any other sense; it is the 'broadband' sensory pathway to understanding. Our reliance on visual perception seems obvious but its implications for information analysts are enormous. This ability of the human mind to rapidly process visual input makes information visualization a useful and often necessary tool, allowing us to turn data into knowledge and insight.

Information visualization is the representation of selected features of complex multi-dimensional data. All kinds of data can be used to create a visualization, including text, image data, sound, voice, video - and of course, all kinds of numerical data. Our visual analysis systems are not static images but highly interactive analytical environments, allowing users to explore, discover, and learn; subset the data, run queries, do time sequence studies, create categories and correlations of data type, and more.

As you can see from our publications, PNNL has been leading the way in information visualization. In 2004, the Department of Homeland Security chose PNNL as the home for the National Visualization and Analytics Center (NVAC)™ . The ambitious goal of NVAC is to define the national research agenda for the field of visual analytics, which addresses the additional challenges of analytic methodology, data representation, and production and dissemination of results.

Who uses Information Visualization?

Our current client base includes users in the fields of:

  • Battlefield Awareness
  • Competitive Intelligence
  • Enterprise Knowledge Management
  • Environmental Security
  • Intellectual Asset Management
  • Intelligence Analysis
  • Law Enforcement
  • Market Assessment
  • Medical Informatics
  • Medical Research
  • Nuclear Non-Proliferation
  • Research Program Management
  • Science and Technology Scanning
  • Translingual Text Analysis

How is it done?

Visualization can be used with virtually any kind of information. The process used in developing a visualization consists of the following steps:

  1. Identify the "features" you wish to visualize. For example, one useful feature for textual data is conceptual terms that can serve as effective discriminators between documents. IN-SPIRE's main visualizations take advantage of such terms. Entities and relationships are other useful textual features.
  2. Create a numerical representation of the features you have selected.
  3. Map the numerical representation into a 2D or 3D visualization.
  4. Integrate tools for exploring and interacting with the visualization.