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Major advances in sequencing technology have produced an avalanche of biological data over the past 12 years. The bottleneck in discovery has consequently shifted from data generation to data analysis, suggesting that much data is not used to its full potential \cite{Lockhart_Winzeler_2000}.  Crowdsourcing is one technique to gain more insight from existing biological data. Putting the diverse eyes and hands of the general public to the purpose of bioinformatics is not new \cite{Good_Su_2013} \cite{ld_Allison_Bonneau_et_al__2012}; examples include protein \cite{lane2012milliseconds} and RNA folding, folding [http://eterna.cmu.edu/web/],  and both paid (Ingenuity® Systems, www.ingenuity.com) and unpaid \cite{hingamp2008metagenome} curation of literature. Rather than approach a problem strictly as professionals, we developed an Open Source DIY workshop where scientists and the public worked together to tackle a synthetic biology project resulting in a publishable outcome. The problem to be solved would need data from completely open sources and not require difficult analysis. Thus we decided to survey of plant translation initiation motifs, aiming to create an open source parts list for controlling translation in metabolic engineering and synthetic biology.