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The Status Quo of FAIR Data Sharing in Psychology

This article is a preprint and has not been certified by peer review [What does this mean?].

Author(s) / Creator(s)

Bittermann, André
Loehlein, Anna M.
Omieczynski, Christian
Lauer, Tim
Gollwitzer, Mario
Sassenberg, Kai

Abstract / Description

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.

Keyword(s)

open data open science data reuse FAIR assessment data archiving citation impact journal guidelines

Persistent Identifier

Date of first publication

2025-10-16

Publisher

PsychArchives

Citation

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  • Author(s) / Creator(s)
    Bittermann, André
  • Author(s) / Creator(s)
    Loehlein, Anna M.
  • Author(s) / Creator(s)
    Omieczynski, Christian
  • Author(s) / Creator(s)
    Lauer, Tim
  • Author(s) / Creator(s)
    Gollwitzer, Mario
  • Author(s) / Creator(s)
    Sassenberg, Kai
  • PsychArchives acquisition timestamp
    2025-10-16T07:27:56Z
  • Made available on
    2025-10-16T07:27:56Z
  • Date of first publication
    2025-10-16
  • Abstract / Description
    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.
    en
  • Publication status
    other
  • Review status
    notReviewed
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/16683
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.21290
  • Language of content
    eng
  • Publisher
    PsychArchives
  • Is related to
    https://hdl.handle.net/20.500.12034/11110
  • Is related to
    https://www.psycharchives.org/handle/20.500.12034/17485
  • Keyword(s)
    open data
  • Keyword(s)
    open science
  • Keyword(s)
    data reuse
  • Keyword(s)
    FAIR assessment
  • Keyword(s)
    data archiving
  • Keyword(s)
    citation impact
  • Keyword(s)
    journal guidelines
  • Dewey Decimal Classification number(s)
    150
  • Title
    The Status Quo of FAIR Data Sharing in Psychology
    en
  • DRO type
    preprint
  • Leibniz institute name(s) / abbreviation(s)
    ZPID