"The increasing volume, complexity, and interconnectedness of published studies in neuroscience make it difficult to determine what is known, what is uncertain, and how to contribute effectively to one’s field. There is a pressing need to develop automated strategies to help researchers navigate the vastness of the published record. Simplified, interactive, and unbiased representations of previous findings (i.e., research maps) would be invaluable in preparing research surveys, in guiding experiment planning, and in evaluating research plans and contributions. Principles normally used in weighing research findings, including reproducibility and convergence, could be automated and incorporated into research maps. Here, we discuss a series of recent advances that are bringing us closer than ever to being able to derive systematic, comprehensive, but also interactive and user-friendly research maps. These maps could revolutionize the way we review the literature, plan experiments, and fund and publish science."