The Status Quo of FAIR Data Sharing in Psychology

Data sharing is paramount for reproducible science, yet few studies have examined whether shared data meet FAIR (findable, accessible, interoperable, reusable) principles, often relying on small journal samples. Hence, we conducted a comprehensive analysis of 11,384 psychology datasets (2013–2024) indexed in PsycInfo and PSYNDEX, assessing FAIRness with the F-UJI tool. While data sharing has increased, FAIRness remained limited: datasets were generally findable and interoperable but less accessible and reusable. FAIRness varied mainly by repository, but not substantially by year, subfield, journal, or author characteristics. Higher reusability was linked to increased citation rates. Compared with F-UJI, humans rated datasets higher for accessibility but lower for interoperability and reusability. To improve data FAIRness, we provide a brief checklist for editors and reviewers that adds practical guidance beyond F-UJI. Finally, we highlight the value of coordinated efforts by repositories, authors, and journals. notReviewed other