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Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
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The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis.

Giuliana Spadaro1,2, Ilaria Tiddi3, Simon Columbus1,4

  • 1Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam.

Perspectives on Psychological Science : a Journal of the Association for Psychological Science
|May 17, 2022
PubMed
Summary
This summary is machine-generated.

The Cooperation Databank (CoDa) enables machine-driven meta-analyses by standardizing human cooperation study data. This platform enhances scientific practice through accessible data and advanced analytical tools.

Keywords:
cooperationdatabankknowledge representationmeta-analysisontologiessocial dilemmas

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Area of Science:

  • Social Sciences, Psychology, Computational Social Science

Background:

  • Scientific publishing traditionally lacks machine-readable formats, hindering large-scale data synthesis.
  • Meta-analyses are crucial for consolidating research findings but are often time-consuming and manual.
  • Understanding human cooperation requires integrating diverse studies across various contexts.

Purpose of the Study:

  • To develop a machine-readable databank and research platform for human cooperation studies.
  • To enable on-demand meta-analyses and advanced statistical analyses of cooperation research.
  • To create a semantically enhanced technological infrastructure for scientific knowledge discovery.

Main Methods:

  • Compiled the Cooperation Databank (CoDa) with 2,636 studies (1958-2017) on human cooperation.
  • Annotated studies using 312 variables and 13,959 quantitative results.
  • Developed a cooperation research ontology and a platform for data retrieval, visualization, and analysis.

Main Results:

  • CoDa contains data from 356,283 participants across 78 societies.
  • The platform supports meta-analyses, metaregressions, publication bias estimation, and power analyses.
  • Visualization tools allow exploration of the cooperation research ontology and citation networks.

Conclusions:

  • Publishing in standardized, machine-readable formats can revolutionize scientific practice.
  • The Cooperation Databank and platform offer a model for future data-driven scientific inquiry.
  • CoDa enhances the accessibility and analytical capabilities of human cooperation research.