While scholars of scientific communication have identified many potential biases that might affect the quality and neutrality of peer reviews [see Weller (2001) and Lee et al. (2013) for reviews of this literature], peer review is still recognized within most research institutions as the best method for evaluating the merits of scientific work.

A growing challenge to peer review is the increasing importance of digital datasets and computational research methods within scientific research. The increased emphases by funding agencies and research organizations are pushing scientific communities toward new approaches for data sharing, management, and preservation (Overpeck et al. 2011). Methods for assessing and ensuring data quality are also taking on new importance to engender trust in data and to enable secondary data use.