Pacific Northwest National Laboratory (PNNL) is a Department of Energy Office of Science national
laboratory that solves complex problems in energy, national security and the environment and advances
scientific frontiers in the chemical, biological, materials, environmental and computational sciences.
Customer Case Description
PNNL was asked by the Department of Homeland Security to participate in a pilot program. The goal
was to pilot an analytical application for the Immigration and Customs Enforcement (ICE) department
that would leverage analysis techniques used for unstructured text analysis with those used in structured
data analysis. PNNL’s primary objectives over the project were threefold:
- Provide a new capability for structured and unstructured data analysis,
- Evaluate/characterize ICE data, and
- Be deployable within eighteen months.
Gus Calapristi, the project’s lead, notes that there are many tools for either unstructured or structured
data analysis. PNNL wanted to address the question of mixed data: information typically found in structured
forms with annotations, case files, reports, etc. Said Calapristi during a presentation to a VAC Consortium
Meeting, “we wanted to ensure data sharing and interoperability and to facilitate data exchange between
specialized tools. We wanted to build upon the known strengths of current technologies. This would give us
the potential for earlier field deployment and user acceptance as well as compatibility with wider toolsets.”
Since PNNL was already using standalone analysis applications for managing and reviewing its unstructured
data, it needed to identify a structured data analysis tool that would seamlessly integrate with the
preexisting analysis technology and provide new ways to visually organize and present information.
PNNL chose Tableau to help blend analysis of structured and unstructured data while simultaneously
fulfilling the data visualization and presentation requirements. Throughout the lengthy pilot, PNNL
is using Tableau coupled with In-Spire, a tool for unstructured data analysis, in simulated real-world
environments in order to assess the following factors:
- Ease of use (minimal time requirement and intellectual investment),
- Ability to integrate into the existing infrastructure, and
- Ability to improve current processes.
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