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The quality of open datasets shared by researchers in ecology and evolution is moderately repeatable and slow to change

We assessed the quality of 362 open datasets shared by 100 principal investigators (PIs) in ecology and evolution to identify predictors of data quality. Datasets generally scored low on completeness and reusability, but these metrics were slightly higher for more recently archived datasets and PIs with less seniority. Journal data sharing policies had no effect on data quality, whereas PI identity explained the largest proportion of the variance in both data completeness (27.8%) and reusability (22.0%), suggesting that a PI’s training and lab culture are key determinants of data quality. Thus, greater incentives and training for individual researchers could help improve data sharing practices.