Data Farming Process and Initial Network Analysis Capabilities
AbstractData 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
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Horne, G.; Meyer, T. Data Farming Process and Initial Network Analysis Capabilities. Axioms 2016, 5, 4.
Horne G, Meyer T. Data Farming Process and Initial Network Analysis Capabilities. Axioms. 2016; 5(1):4.Chicago/Turabian Style
Horne, Gary; Meyer, Theodore. 2016. "Data Farming Process and Initial Network Analysis Capabilities." Axioms 5, no. 1: 4.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.