Review of supporting data for research papers:Logic,methodology,and implementation framework
[Purposes]From the perspective of ensuring the testability and reproducibility of research,this paper explores the logic,methodology,and preliminary implementation framework for the review of supporting data in research papers,so as to provide a foundation for establishing an evidence-based operational,fine-grained verifiable,and automatically computable review mechanism for supporting data.[Methods]Based on the basic principles of scientific research reliability in the field of science and scientific journals,we briefly summarized the policies and practices of supporting data in research papers.Then,we used systematic analysis and evidence-based design methods to systematically design and establish principles,architecture,indicators,and implementation suggestions for supporting data review.[Findings]The principle mechanism is built based on computable chain of evidence.A three-step review structure that includes checking data availability statements,the compliance of the supporting data with FAIR principles,and the alignment of the supporting data with the study conclusions is proposed.The study presents a working framework and a first-phase indicator system for reviewing supporting data of research papers that are guidelines-based,operational,measurable,evaluable,and computable.[Conclusions]The study helps improve the systematic,transparent,and evaluable review process of supporting data for research papers,thus enhancing implementation efficiency and promoting the quality of peer review.
Research reliabilitySupporting dataData availability statementFAIRPeer reviewData file reviewData metadata reviewData and conclusion consistency reviewComputable chain of evidence