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Data Farming Process and Initial Network Analysis Capabilities

1,†,* and 2,†
Blue Canopy Group, 4924 Andrea Avenue, Annandale, VA 22003, USA
Meyercraft, Inc., McLean, VA 22101, USA
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editors: Frank Emmert-Streib and Stefan Pickl
Received: 9 December 2015 / Revised: 13 January 2016 / Accepted: 20 January 2016 / Published: 27 January 2016
(This article belongs to the Special Issue Data Farming: Mathematical Foundations and Applications)
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Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics. View Full-Text
Keywords: data farming; network analysis; social networks; modeling; simulation; agent based modeling data farming; network analysis; social networks; modeling; simulation; agent based modeling

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Horne, G.; Meyer, T. Data Farming Process and Initial Network Analysis Capabilities. Axioms 2016, 5, 4.

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