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## Introduction  Due to major Major  advances in sequencing technology, technology has produced  an avalanche of biodata has been produced biological data  over the past 12 years. One consequence of these changes is the shifting of the The  bottleneck in discovery has consequently shifted  from data generation to data analysis. This It  raises the persistent persistent,  nagging question that a vanishingly small amount of the data is used to its full potential \cite{Lockhart_Winzeler_2000}. One part technique  ofthe solution to  gaining more insight from existing biodata biological data  could be crowdsourcing. Putting the many and varied  eyes and hands of the general public to the purpose of mining, organizing or analyzing biological data has surfaced several times in bioinformatics \cite{Good_Su_2013} \cite{ld_Allison_Bonneau_et_al__2012}. Examples of problems approached by crowdsourcing include protein [ref] and RNA folding, both paid [ingenuity] and unpaid [refs] curation of literature. Rather than engage this problem strictly as professionals, an Open Source DIY workshop was presented 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 look at 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.