TECHNOLOGY AREA(S): Information Systems

ACQUISITION PROGRAM: None or N/A NAE Chief Technology Office

OBJECTIVE: Evaluate the benefits of big data analytics to effectively manage the abundance of ingested and disparate data for the purpose of enhancing the decision-making process during maritime missions.

DESCRIPTION: The success of military operations significantly depends on the level of situational awareness. This is especially true for the P-8A Poseidon conducting long-range anti-submarine warfare; anti-surface warfare; and intelligence, surveillance, and reconnaissance (ISR) maritime missions. An expanding array of sensors and disparate information sources has exponentially increased the sheer volume and variety of data flooding operators and potentially causing operator fatigue from data overload. The P-8A will process and analyze terabytes of data per mission, a significant increase from the gigabytes of data for its predecessor, the P-3. At risk is the effectiveness and efficiency of on-board operators to manage, interpret, and take action on timely sensitive data to neutralize potential threats.

Actionable intelligence enables the aviator to rapidly make informed decisions and respond more quickly to ever changing events. This requires the automated processing of large and varied data to include imagery, acoustic, environmental, intelligence, and historical habit patterns to uncover hidden and unknown correlations to predict target actions. Implementation of big data analytics to perform maritime data mining and predictive analytics will enable mission commanders to exploit the information to make real-time and informed decisions in a maritime operational environment.

Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by DoD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Security Service (DSS). The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this project as set forth by DSS and NAVAIR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advanced phases of this contract.

PHASE I: Develop, design, and demonstrate a strategy, taking into consideration the feasibility, suitability and acceptability, to leverage big data analytics for P-8A maritime missions. Identify potential roadblocks likely to be encountered and formulate approaches to overcome them. Recommend an architecture, such as open source, and implementation plan and illustrate the benefits of big data analytics through operational use cases. The Phase I effort will include prototype plans to be developed under Phase II.

PHASE II: Develop a working prototype of the selected concept to include high level requirements, design, initial testing, and demonstration. Demonstrate the prototype in a lab or live environment.

Work in Phase II may become classified. Please see Description for details.

PHASE III DUAL USE APPLICATIONS: Conduct integration and testing of the prototype for the P-8A system, to include land-based mobile operational centers (MOCs), where data analysis occurs. This capability would have multiple applications for the private sector where large amounts of data need analysis for efficiency of specific systems, to include banking, inventory, and commerce.

REFERENCES:

1. Agrawal, D., Bernstein, P., Bertino, E., Davidson, S., Dayal, U., Franklin, M., and Widom, J. �Challenges and Opportunities with Big Data: A white paper prepared for the Computing Community Consortium committee of the Computing Research Association.� 2012. https://cra.org/ccc/wp-content/uploads/sites/2/2015/05/bigdatawhitepaper.pdf

2. Porche III, I., Wilson, B., Jonhson, E.-E., Tierney, S., and Saltzman, E. �data_flood: Helping the Navy Address the Rising Tide of Sensor Information.� RAND Corporation: Santa Monica. https://www.rand.org/content/dam/rand/pubs/research_reports/RR300/RR315/RAND_RR315.pdf

3. Ramos, J., and Ranjan, R. �Cognitive Data Governance Powered by Machine Learning to Find and Use Governed Data.� IBM Corporation: Somers, NY, 2018.� https://kapost-files-prod.s3.amazonaws.com/uploads/asset/file/5b0440c579aff3001d0000be/CDG_Jo_Rakesh.pdf

KEYWORDS: Big Data; Analytics; Decision Making; Automation; Disparate Sources; Computation