Biocuration is a time-intensive process that involves extraction, transcription, and organization of biological or clinical data from disjointed data sets into a user-friendly database. Curated data is subsequently used primarily for text mining or informatics analysis (bioinformatics, neuroinformatics, health informatics, etc.) and secondarily as a researcher resource. Biocuration is traditionally considered a Ph.D. level task, but a massive shortage of curators to consolidate the ever-mounting biomedical “big data” opens the possibility of utilizing biocuration as a means to mine today’s data while teaching students skill sets they can utilize in any career. By developing a biocuration assembly line of simplified and compartmentalized tasks, we have enabled biocuration to be effectively performed by a hierarchy of undergraduate students. We summarize the necessary physical resources, process for establishing a data path, biocuration workflow, and undergraduate hierarchy of curation, technical, information technology (IT), quality control and managerial positions. We detail the undergraduate application and training processes and give detailed job descriptions for each position on the assembly line. We present case studies of neuropathology curation performed entirely by undergraduates, namely the construction of experimental databases of Amyotrophic Lateral Sclerosis (ALS) transgenic mouse models and clinical data from ALS patient records. Our results reveal undergraduate biocuration is scalable for a group of 8–50+ with relatively minimal required resources. Moreover, with average accuracy rates greater than 98.8%, undergraduate biocurators are equivalently accurate to their professional counterparts. Initial training to be completely proficient at the entry-level takes about five weeks with a minimal student time commitment of four hours/week.
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