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Data Farming combines the rapid prototyping capability inherent in certain simulation models with the exploratory power of high performance computing to rapidly generate insight into questions. The Data Farming process focuses on a more complete landscape of possible system responses, rather than attempting to pinpoint an answer. Data Farming allows decision makers to more fully understand the landscape of possibilities and also consider outliers that may be discovered. Over the past decade, an international community has formed around these ideas. In 2008, International Data Farming Workshop 16 took place in Monterey, California, USA and workshop number 17 was held in Garmisch Partenkirchen, Germany. In addition to a summary of these two workshops, this paper will present an overview of the process that has developed to include the development of both methods and applications in the International Data Farming Community.