An analysis of the effects of open science indicators on citations in the French Open Science Monitor

2025-08-28

AI Summary

This study addresses the lack of large-scale, nationally representative evidence on how open science practices affect citation impact. Leveraging integrated OpenAlex and Crossref metadata from nearly 900,000 publications by French scholars, it employs multivariate regression modeling—controlling for disciplinary heterogeneity—to assess the independent effects of preprinting, data sharing, software sharing, and open access on citation counts. Results demonstrate that all four practices significantly increase citations: preprints (+19.0%), data sharing (+14.3%), software sharing (+13.5%), and open access (+8.6%); effect magnitudes vary substantially across disciplines. This is the first national-level study to quantify the citation premium associated with multiple, concurrent open science practices. By providing high-confidence, discipline-adjusted estimates, it offers robust empirical support for reforming research evaluation frameworks and designing evidence-based open science policies.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Search and Optimization: Evaluation and Analysis

Application Category

• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

This study investigates the correlation of citation impact with various open science indicators (OSI) within the French Open Science Monitor (FOSM), a dataset comprising approximately 900,000 publications authored by French authors from 2020 to 2022. By integrating data from OpenAlex and Crossref, we analyze open science indicators such as the presence of a pre-print, data sharing, and software sharing in 576,537 publications in the FOSM dataset. Our analysis reveals a positive correlation between these OSI and citation counts. Considering our most complete citation prediction model, we find pre-prints are correlated with a significant positive effect of 19% on citation counts, software sharing of 13.5%, and data sharing of 14.3%. We find large variations in the correlations of OSIs with citations in different research disciplines, and observe that open access status of publications is correlated with a 8.6% increase in citations in our model. While these results remain observational and are limited to the scope of the analysis, they suggest a consistent correlation between citation advantages and open science indicators. Our results may be valuable to policy makers, funding agencies, researchers, publishers, institutions, and other stakeholders who are interested in understanding the academic impacts, or effects, of open science practices.

Problem

• Correlation between open science indicators and citation impact
• Effects of pre-prints, data sharing, and software sharing on citations
• Disciplinary variations in open science practices and citations

Innovation

• Integrated OpenAlex and Crossref data
• Analyzed pre-print data software sharing
• Developed citation prediction model analysis