Data Analytics
Sandia National Laboratories: Synthetic Apperature Radar (SAR): SAR Hardware
PANTHER - Pattern ANalytics To support High-performance Exploitation and Reasoning

Sandia has built a strong capability in data analytics to support its many national security programs

"Obviously, it's not the data per se that create value...what really matters is our ability to derive from them new insights, to recognize relationships, to make increasingly accurate predictions. Our ability, that is, to move from data to knowledge to action."

- John Holdren, Director,
White House Office of Science and Technology Policy,
March 29, 2012


SAR Connect
Enabling and building advocacy for the use of Synthetic Aperture Radar (SAR).

Sandia’s Data Analytics Innovation Cell is focused on developing the next generation technologies necessary to elevate the intelligence analyst’s ability to work at a higher level of abstraction with complex and large data sets in the development of intelligence to support of national security. The primary foci of the Data Analytics Innovation Cell include a) trajectory representations and analytics, b) automatic static and ephemeral feature detections in synthetic aperture radar imagery, c) geo-spatial, temporal semantic graph representations of multi-int sensor data and associated search capabilities, and d) human analyst performance and visual representations in support of sense making.

The Next Generation of data representations

Rethinking Patterns in Motion

  • Geometric and temporal trajectory analyses - changing dots to tracks to trajectories
  • Geospatial-temporal relationships - i.e., identifiying things like co-travelers

Rethinking Traditional GIS and Geospatial Search

  • Compact, efficient representations of features extrade from sensor data.
  • Sensor agnostic capability for multi-INT feature relationships in time and space.
  • Predictive and forensic analysis

Analysts care about "what," "where," and "when." Where is it going? Where has it been? What's the relationship? What's changed?

Removing workloads from the analyst

Currently, analysts search, locate and visualy inspect data sets but in the future, when moving away from the data domain, abstract data representations will support analyst queries as part of discovery & disambiguation.

The future analysts will work with information rather than data, elevating their ability to develop actionable intelligence.

Developing new mission-centric workflows

Do existing analytic workflows really need what we're developing? Or, will geospatial pattern analytics spur evolution of novel analytic workflows, forms of expertise, and analytic products?

PANTHER is working with partner agencies to develop novel analytic workflows around real-world problems to answer questions like...

  • What would a geospatial-temporal pattern analytic workflow look like?
  • Where might it fit in an existing organization?
  • Who are its customers?
  • Who works in this cell?
  • What would this produce? On what timelines?
  • How does this cell's work complement/augment existing analytic workflows in other areas of the DoD/IC?