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Axioms 2016, 5(1), 8; doi:10.3390/axioms5010008

Summary of Data Farming

1
Blue Canopy Group, 11091 Sunset Hills Road, Suite 777, Reston, VA 20190, USA
2
Airbus Defence and Space, Claude-Dornier-Str., Immenstaad 88090, Germany
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Frank Emmert-Streib
Received: 7 January 2016 / Revised: 9 February 2016 / Accepted: 15 February 2016 / Published: 1 March 2016
(This article belongs to the Special Issue Data Farming: Mathematical Foundations and Applications)
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Abstract

Data Farming is a process that has been developed to support decision-makers by answering questions that are not currently addressed. Data farming uses an inter-disciplinary approach that includes modeling and simulation, high performance computing, and statistical analysis to examine questions of interest with a large number of alternatives. Data farming allows for the examination of uncertain events with numerous possible outcomes and provides the capability of executing enough experiments so that both overall and unexpected results may be captured and examined for insights. Harnessing the power of data farming to apply it to our questions is essential to providing support not currently available to decision-makers. This support is critically needed in answering questions inherent in the scenarios we expect to confront in the future as the challenges our forces face become more complex and uncertain. This article was created on the basis of work conducted by Task Group MSG-088 “Data Farming in Support of NATO”, which is being applied in MSG-124 “Developing Actionable Data Farming Decision Support for NATO” of the Science and Technology Organization, North Atlantic Treaty Organization (STO NATO). View Full-Text
Keywords: modeling and simulation; data generation; rapid scenario prototyping; distillation model development; design of experiments; high performance computing; data analysis and visualization; data mining; collaboration modeling and simulation; data generation; rapid scenario prototyping; distillation model development; design of experiments; high performance computing; data analysis and visualization; data mining; collaboration
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Horne, G.; Schwierz, K.-P. Summary of Data Farming. Axioms 2016, 5, 8.

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