Technical Abstract: We report a strategy for consensus QTL maps that leverages the highly curated data in MaizeGDB, in particular, the numerous QTL studies and maps that are integrated with other genome data on a common coordinate system. In addition, we exploit a systematic QTL nomenclature and a hierarchical categorization of over 400 maize traits developed in the mid 90’s; the main nodes of the hierarchy align with the trait ontology at Gramene, a comparative mapping database for cereals. Consensus maps are presented for one trait category, insect response (80 QTL); and two traits, grain yield (71 QTL) and kernel weight (113 QTL), representing over 20 separate QTL map sets of 10 chromosomes each. Because these data are in the central repository for maize map and sequence data, investigators immediately gain access to tools for marker assisted selection, higher resolution mapping and candidate gene discovery.