Most scientific investigators conduct well-designed and controlled preclinical experiments generating data that are difficult to explain, contrast with existing scientific dogma, or represent a perceived negative result. It is common for these findings to remain hidden away in a drawer from the greater scientific community. However, these unseen results can lead to publication bias, have the potential to significantly advance scientific disciplines if they are published, and can help investigators avoid repeating experiments that have already been done, thus saving money and time. Moreover, these unexpected data may actually have significance if re-interpreted leading to new hypotheses. This editorial commentary highlights a novel user-friendly tool developed by Bernard and colleagues (Clin Sci (Lond) (2020) 134 (20): 2729–2739) to help investigators determine appropriate options for disseminating unpublished data in order to make them available to the broader scientific community. In addition, this commentary serves as an announcement for an upcoming special call for papers on meta-research to be published in Clinical Science. Meta-research is the evaluation and study of existing scientific literature and data. It is an evolving field dedicated to improving rigor and reproducibility in science, an endeavor to which Clinical Science and Portland Press are committed.