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Techniques to Adjust Computational Trends Involving Changing Data (TACTIC-D)

Description:

TECHNOLOGY AREA(S): Air Platform 

OBJECTIVE: Develop technology based on statistical or computational methods to assist in the continued tracking of training performance and proficiency trends as underlying tactical data changes. 

DESCRIPTION: There is a push by the DoD and USN to leverage the benefits of qualitative analysis by consuming large data sources (e.g., aviation data logs) and implementing human performance assessment and tracking of tactically relevant data to better understand force proficiency. To support decision making, big data analytics focused on developing trends or predictions based on historical data is desired. Military domains for big data is unique in that the tactics, techniques and procedures used by the fleet shift over time due to changes in capabilities or the need to adapt to novel or updated tactics by opposing forces. This creates a unique challenge for the typical statistics that would be leveraged in big data sources, as taking these changes into account is necessary to ensure that comparisons remain meaningful. The continued push for integrated warfare will likely result in cross-platform, mission-based trends; however, there may be differences in constructs across platforms (e.g., one platform may rely on timeliness and another on accuracy) that if not accounted for in the analysis or development of common construct definitions would skew analysis results. This effort seeks to identify statistical or computational methods that can assist with these adjustments to statistical trends, and implement them in an automated tool that will allow for the timely and continued calculation of trends related to fleet performance and proficiency. 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: Refine or develop methods for adjusting calculations as data points related to tactics, techniques and procedures change. Test the feasibility of implementing any identified/developed methods and to identify the benefits and limitations of each. 

PHASE II: Implement automated support through algorithms or other computational processes for implementing feasible methods for adjusting data. Develop usable computer interfaces that allow end users to make note of data points being adjusted as time shifts. Ensure that data results identify any potential limitations of calculations based on early methodological testing to ensure decision makers understand the comparisons. Implement a safeguard that alerts users to the extent to which trend analysis can be continued before the comparisons are meaningless due to lack of continuity of data sources, and implement tools to assist users with re-base lining data in these situations. 

PHASE III: Extend the baseline functionality to include advanced or more robust data analysis techniques, and/or integrate developed capability with existing database and analysis systems. Implement Risk Management Framework (RMF) guidelines to support information assurance compliance, including updates to support installation on stand alone or Navy Marine Corps Intranet (NMCI) systems. Coordinate with partners or customers of commercial applications of the technology solution developed. Big data analytics has been implemented in a range of other domains such as athletics and medical communities. For the latter or other quickly advancing domains due to the pace at which technology support changes, novel techniques developed under this topic or integration of technology solutions such as those proposed here may provide unique insights for other domains leverage big data analytics. Private Sector Commercial Potential: Big data analytics has been implemented in a range of other domains such as athletics and medical communities. For the latter or other quickly advancing domains due to the pace at which technology support changes, novel techniques developed under this topic or integration of technology solutions such as those proposed here may provide unique insights for other domains leverage big data analytics. 

REFERENCES: 

Big Data, new epistemologies and paradigm shifts: http://bds.sagepub.com/content/1/1/2053951714528481.full.pdf+html

Challenges of Big Data Analysis: http://nsr.oxfordjournals.org/content/1/2/293.short

Example commercial off the shelf technologies: http://www.predictiveanalyticstoday.com/bigdata-platforms-bigdata-analytics-software/#content-anchor

Challenges and Opportunities with Big Data: http://dl.acm.org/citation.cfm?id=2367572

 

KEYWORDS: Qualitative Analysis; Big Data Analysis; Human Performance Assessment; Data Trends; Data Predictions; Statistical Analysis 

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