Publishing studies using standardized, machine-readable formats will enable machines to perform meta-analyses on demand. To build a semantically enhanced technology that embodies these functions, we developed the Cooperation Databank (CoDa)—a databank that contains 2,636 studies on human cooperation (1958–2017) conducted in 78 societies involving 356,283 participants. Experts annotated these studies along 312 variables, including the quantitative results (13,959 effects). We designed an ontology that defines and relates concepts in cooperation research and that can represent the relationships between results of correlational and experimental studies. We have created a research platform that, given the data set, enables users to retrieve studies that test the relation of variables with cooperation, visualize these study results, and perform (a) meta-analyses, (b) metaregressions, (c) estimates of publication bias, and (d) statistical power analyses for future studies. We leveraged the data set with visualization tools that allow users to explore the ontology of concepts in cooperation research and to plot a citation network of the history of studies. CoDa offers a vision of how publishing studies in a machine-readable format can establish institutions and tools that improve scientific practices and knowledge.

中文翻译：

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合作数据库：机器可读科学加速研究综合

使用标准化的机器可读格式发布研究将使机器能够按需执行荟萃分析。为了构建体现这些功能的语义增强技术，我们开发了合作数据库（CoDa）——一个包含 2,636 项人类合作研究（1958-2017）的数据库，在 78 个社会中进行，涉及 356,283 名参与者。专家们用 312 个变量对这些研究进行了注释，包括定量结果（13,959 个效应）。我们设计了一个本体来定义和关联合作研究中的概念，并且可以表示相关研究和实验研究结果之间的关系。我们创建了一个研究平台，在给定数据集的情况下，用户可以检索通过合作测试变量关系的研究，可视化这些研究结果，并执行 (a) 元分析，(b) 元回归，(c) 发表偏倚估计，以及 (d) 未来研究的统计功效分析。我们利用数据集和可视化工具，允许用户探索合作研究中概念的本体，并绘制研究历史的引文网络。CoDa 提供了一个愿景，即以机器可读格式发表研究可以建立改善科学实践和知识的机构和工具。