For any scientific report, repeating the original analyses upon the original data should yield the original outcomes. We evaluated analytic reproducibility in 25 Psychological Science articles awarded open data badges between 2014 and 2015. Initially, 16 (64%, 95% confidence interval [43,81]) articles contained at least one ‘major numerical discrepancy' (>10% difference) prompting us to request input from original authors. Ultimately, target values were reproducible without author involvement for 9 (36% [20,59]) articles; reproducible with author involvement for 6 (24% [8,47]) articles; not fully reproducible with no substantive author response for 3 (12% [0,35]) articles; and not fully reproducible despite author involvement for 7 (28% [12,51]) articles. Overall, 37 major numerical discrepancies remained out of 789 checked values (5% [3,6]), but original conclusions did not appear affected. Non-reproducibility was primarily caused by unclear reporting of analytic procedures. These results highlight that open data alone is not sufficient to ensure analytic reproducibility.

对于任何科学报告，对原始数据重复原始分析应该产生原始结果。我们评估了2014 年至 2015 年间荣获开放数据徽章的 25 篇心理科学文章的分析重现性。最初，16 篇（64%，95% 置信区间 [43,81]）文章至少包含一个“重大数值差异”（>10% 差异））促使我们请求原作者提供意见。最终，9 (36% [20,59]) 篇文章的目标值无需作者参与即可重现；在作者参与下，6 篇 (24% [8,47]) 篇文章可重现；无法完全重现，有 3 篇 (12% [0,35]) 篇文章没有作者的实质性回应；尽管作者参与了 7 篇 (28% [12,51]) 篇文章，但仍不能完全重现。总体而言，789 个检查值中仍有 37 个主要数值差异（5% [3,6]），但原始结论似乎并未受到影响。不可重复性主要是由于分析程序报告不明确造成的。这些结果表明，仅开放数据不足以确保分析的再现性。