Spadaro, G., Tiddi, I., Columbus, S., Jin, S., Ten Teije, A., CoDa Team, & Balliet, D. (in press). The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis. Perspectives on Psychological Science, 17(5), 1472–1489. https://doi.org/10.1177/17456916211053319
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, 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. We leveraged the dataset 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.
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.