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 2,641 studies on human cooperation (1958-2017) published in Chinese, English, and Japanese. Experts annotated these studies for 312 variables, including the quantitative results (effect sizes). We designed an ontology that defines and relates concepts in cooperation research and that can represent the relationships between individual study results. We have created a research platform that, based on the dataset, enables users to retrieve studies that test the relation of variables with cooperation, visualize these study results, and perform (1) meta-analyses, (2) meta-regressions, (3) estimates of publication bias, and (4) statistical power analyses for future 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.
The process of creating the Cooperation Databank (CoDa).
The steps were performed in the presented order, but there was some feedback and iterations that occurred between specific steps. For example, some changes to the semantic modeling were made based on knowledge acquired during the annotation of studies.