Journal Research Data Policies in Materials Science

TL;DR

This study surveys research data policies in 171 materials science journals, revealing progress yet highlighting gaps in enforceability, data sharing, and software practices, and proposing future best practices.

Contribution

It provides a comprehensive analysis of current journal data policies in materials science, identifying strengths, weaknesses, and variability across publishers and impact factors.

Findings

Most journals have research data policies, but enforceability is limited.

Public data deposition is rarely mandatory, and FAIR principles are often only encouraged.

Software sharing policies are less developed than data policies.

Abstract

Open and reproducible research in materials science relies on the availability of data, code, and common metadata standards. Journal research data policies (RDPs) remain a primary mechanism by which publication norms are defined and enforced. We survey RDPs for 171 materials science journals spanning 17 publishers, using an expanded coding framework that captures both data-and-code sharing behavior as well as refereeing standards. We find clear signs of progress in comparison to earlier research on RDPs: nearly all journals provide an RDP, and most mention data availability statements. However, enforceable requirements remain uncommon, public deposition of underlying data is rarely mandatory, and FAIR publication is typically encouraged rather than required. Expectations for research software are substantially less developed than those for data, with limited attention to versioning and persistent identifiers, dependency disclosure, reproducible execution environments, or software quality practices. Aggregating the findings on policy features into an open research data score reveals pronounced heterogeneity across journals. Neither impact factor nor access model reliably predicts policy strength. Double-coding further shows that more complex policies and stricter policies can be more challenging to interpret consistently, and we highlight challenges in consistent RDP encoding across studies. Lastly, we conclude with recommended best practice directions for the future.