This chapter explores existing data reproducibility and robustness initiatives from a cross-section of large funding organizations, granting agencies, policy makers, journals, and publishers with the goal of understanding areas of overlap and potential gaps in recommendations and requirements. Indeed, vigorous stakeholder efforts to identify and address irreproducibility have resulted in the development of a multitude of guidelines but with little harmonization. This likely results in confusion for the scientific community and may pose a barrier to strengthening quality standards instead of being used as a resource that can be meaningfully implemented. Guidelines are also often framed by funding bodies and publishers as recommendations instead of requirements in order to accommodate scientific freedom, creativity, and innovation. However, without enforcement, this may contribute to uneven implementation. The text concludes with an analysis to provide recommendations for future guidelines and policies to enhance reproducibility and to align on a consistent strategy moving forward.
Keywords: Data quality; Good research practice; Guidelines; Preclinical; Reproducibility.