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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, and it raises the question that only a small amount of total data is used to its full potential \cite{Lockhart_Winzeler_2000}.   One technique to gain more insight from existing biological data may be crowdsourcing. Putting the diverse eyes and hands of the general public to the purpose of mining, organizing or analyzing biological data has previously surfaced in bioinformatics \cite{Good_Su_2013} \cite{ld_Allison_Bonneau_et_al__2012}. Examples of problems approached by crowdsourcing include protein \cite{lane2012milliseconds} and RNA folding, and both paid (Ingenuity® Systems, www.ingenuity.com) and unpaid [refs] \cite{hingamp2008metagenome}  curation of literature. Rather than approach a problem strictly as professionals, we presented an Open Source DIY workshop where scientists and the public could work together to tackle an introductory synthetic biology project resulting in a publishable outcome. The problem to be solved would need data from completely open sources, not require difficult analysis and ideally examine one or more typical bioinformatics data sources. Thus we decided to do a survey of plant translation initiation motifs which could be embodied as an open source parts list for controlling translation in metabolic engineering and synthetic biology efforts.