LAKE: Large-Scale DAta Storage for Knowledge DiscovEry
Navy SBIR FY2018.1

Sol No.: Navy SBIR FY2018.1
Topic No.: N181-089
Topic Title: LAKE: Large-Scale DAta Storage for Knowledge DiscovEry
Proposal No.: N181-089-0990
Firm: Intelligent Automation, Inc.
15400 Calhoun Drive
Suite 190
Rockville, Maryland 20855
Contact: Bryan Stewart
Phone: (301) 294-4251
Web Site:
Abstract: DCGS-N Inc 2 is the essential follow-on for the DCGS-N Inc 1 program that permits the Navy to leverage the robust sensor investments by the Intelligence Community (IC) and Military Services to significantly improve Battlespace Awareness and decision making. It is an expedited effort to foster more cross-domain interoperability between networks by gathering, integrating, and organizing information from hundreds of sources for analysts looking to interpret combat data, assess terrain information, receive SIGINT feeds, monitor sensor input and collect other kinds of ISR information. It is critical that information agility is achieved at all echelons so that decision-makers receive the right information at the right time. To address the critical need of Multi-Domain Data Management (MDDM), Intelligent Automation, Inc. along with CACI propose to develop a Large-Scale Data Storage for Knowledge Discovery (LAKE) architecture. The key innovation of this proposal is the development of a large data warehousing and analysis tool that is secure, scalable, resilient, and built using state of the art open source tools.
Benefits: The DoD along with several other government organizations (e.g., DHS, DoE, states, etc.) are actively pursuing a LAKE related technology development programs. Examples include Aegis, JSF, F-15E Radar Modernization Program (RMP) and F-15C/D radar update programs. All of these programs require fast access to yearsâ?T worth of historical data in addition to current data. A direct application of LAKE is to help store and parse ORTS and ICAS data in the Aegis program. We have been discussing with our partner, Lockheed Martin, the developer of ORTS, and will explore the possibility and design plans for future integration with ORTS. LAKE will be beneficial for industries that extract information from large volumes of data such as financial investment groups that mine the stock market data and use it to develop algorithms for high frequency trading. Medical research industries invest in data mining tools to identify specific markers during trails to shorten the drug trial cycles. Political groups that mine meta-data to target voters.