The science behind the use of uncertainty factors has progressed considerably. Increased knowledge of inter- and intraspecies sensitivity, mechanisms of action, and detailed evaluation of data bases can support the use of data-derived uncertainty factors, which ultimately results in a risk assessment with greater confidence. Papers that highlight available data for each of several areas of uncertainty are discussed, indicating that choice of the appropriate factor requires scientific judgement on a case-by-case basis. Case studies from EPA and Health Canada risk values illustrate the use of data in chemical specific risk assessments to support the selection of uncertainty factors other than the default value of 10-fold. In the case studies, the types of data that have been used to support a change in the default value are explicitly reviewed, as well as why the data support a different uncertainty factor, how the uncertainty was reduced, and what assumptions have been satisfied or replaced. Incorporation of all available scientific data into the risk assessment process fosters increased research and ultimately reduces uncertainty. The results of this review support the use of data-derived uncertainty factors when appropriate scientific data are available.