Data from: It’s all in the timing: calibrating temporal penalties for biomedical data sharing

Objective: Biomedical science is driven by datasets that are being accumulated at an unprecedented rate, with ever-growing volume and richness. There are various initiatives to make these datasets more widely available to recipients who sign Data Use Certificate agreements, whereby penalties are levied for violations. A particularly popular penalty is the temporary revocation, often for several months, of the recipient’s data usage rights. This policy is based on the assumption that the value of biomedical research data depreciates significantly over time; however, no studies have been performed to substantiate this belief. This study investigates whether this assumption holds true and the data science policy implications.
Methods: This study tests the hypothesis that the value of data for scientific investigators, in terms of the impact of the publications based on the data, decreases over time. The hypothesis is tested formally through a mixed linear effects model using approximately 1200 publications between 2007 and 2013 that used datasets from the Database of Genotypes and Phenotypes, a data-sharing initiative of the National Institutes of Health.
Results: The analysis shows that the impact factors for publications based on Database of Genotypes and Phenotypes datasets depreciate in a statistically significant manner. However, we further discover that the depreciation rate is slow, only ∼10% per year, on average.
Conclusion: The enduring value of data for subsequent studies implies that revoking usage for short periods of time may not sufficiently deter those who would violate Data Use Certificate agreements and that alternative penalty mechanisms may need to be invoked.

研究目标：生物医学科学的进步依赖于各类数据集的支撑，此类数据集正以前所未有的速率持续积累，规模与丰富度均不断提升。目前已有多项举措，旨在将这些数据集更广泛地开放给签署了数据使用证书协议（Data Use Certificate）的数据使用方，协议中明确违规行为将面临相应处罚。其中较为通行的处罚方式为临时收回数据使用方的数据使用权，通常时长可达数月。该政策的核心假设为生物医学研究数据的价值会随时间推移大幅贬值，但目前尚无相关研究对这一假设进行验证。本研究旨在验证该假设是否成立，并探讨其对数据科学政策的影响。
研究方法：本研究将验证如下假设：基于某数据集产出的学术论文的影响力，可反映该数据集对于科研人员的价值，且该价值会随时间推移而降低。本研究采用混合线性效应模型，对上述假设进行正式检验；研究数据来自2007年至2013年间发表的约1200篇学术论文，这些论文均使用了美国国立卫生研究院（National Institutes of Health）数据共享项目——基因型与表型数据库（Database of Genotypes and Phenotypes）的数据集。
研究结果：分析结果显示，基于基因型与表型数据库数据集产出的学术论文，其影响因子随时间推移呈现出具有统计学显著性的贬值趋势。但进一步分析发现，该贬值速率较为平缓，年均仅约为10%。
研究结论：数据集对于后续研究仍具备持久价值，这意味着短期收回数据使用权的处罚方式，不足以对违反数据使用证书协议的行为形成有效威慑，因此亟需探索替代性的处罚机制。