It is important to stimulate innovation for regulatory testing methods. Scrutinizing the knowledge of (un)certainty of data from actual standard in vivo methods could foster the interest in new testing approaches. Since standard in vivo data often are used as reference data for model development, improved uncertainty accountability also would support the validation of new in vitro and in silico methods, as well as the definition of acceptance criteria for the new methods. Hazard and risk estimates, transparent for their uncertainty, could further support the 3Rs, since they may help focus additional information requirements on aspects of highest uncertainty. Here we provide an overview on the various types of uncertainties in quantitative and qualitative terms and suggest improving this knowledge base. We also reference principle concepts on how to use uncertainty information for improved hazard characterization and development of new testing methods.