DIA dives into analytics

The Defense Intelligence Agency hopes to start building its new-age big data transformer -- Machine-Assisted Analytic Rapid-Repository System or MARS -- in fiscal 2020.

A public DIA strategy document describes MARS as an "initiative that will transform the current databases that house foundational military intelligence into an advanced, comprehensive, scalable, flexible, and rigorous intelligence environment for the next century. Ultimately, MARS will create a military intelligence environment for the warfighter and analyst similar to the World Wide Web for consumers."

MARS functional requirements manager, Tom Dillaplain, said the system aims to automate much of what intelligence analysts do now, while inserting them at the most crucial part of the process.

Currently, DIA relies on physical servers spread over various networks and manual data entry.

MARS will be cloud-based, scalable and have edge capability, Dillaplain said during an AFCEA NOVA event June 21.

MARS is coming out of research because DIA is at "the point where there's just simply too much information coming at our analysts," for them to manually assess granular objects, Dillaplain said.

"It would be impossible for us," he said, particularly for supporting cyber operations where granular understanding of relationships among networks and facilities is key. Even with quadruple the number of analysts, the amount of data would still be overwhelming, he said.

"We have access to a lot of information, but we can only display what the analyst puts in the database," he said. Without automation, analysts can only capture a small fraction of data points.

MARS will move from validating an analyst's work to validating an algorithm that can produce intelligence from raw data.

Another MARS goal is to help re-engineer the data environment for several areas -- infrastructure, intelligence, mission data, space and cyberspace -- "instead of replacing one database with a more modern version of that database."

To get there, DIA will need to build analytic services to help with automation, enhance interoperability with mission partners and help push data out. Ultimately, he said, the goal is to create a multi-operational environment where analysts can seamlessly monitor objects as they move.

"The key to successful implementation of artificial intelligence is to place the human at the most useful point in the process. And so we're trying to figure out how to do that as well," he said.

MARS will begin putting out acquisition vehicles in fiscal 2020 to solicit proposals to build it incrementally, Dillaplain said.