About this resource

    Type of resources
    Primary Source, Teaching/Learning Strategy
    Education level(s)
    Graduate / Professional, Career / Technical
    Primary user(s)
    Librarian
    Subject area(s)
    Social Science
    Language(s)
    English
    Cluster
    Transparency and Reproducibility in Computation and Analysis, FAIR Data and Materials
    Last updated
    9 November 2026
    Primary SourceTeaching/Learning Strategy

    10 Things for Curating Reproducible and FAIR Research

    By RDA CURE-FAIR WG (Consortium)

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    Level Graduate / Professional, Career / Technical · For Librarian · Language English

    Abstract

    10 Things for Curating Reproducible and FAIR Research (CURE-FAIR) provides standards-based guidelines to follow CURE-FAIR best practices with regards to publishing and archiving computationally reproducible studies, including the associated computational methods and materials. The 10 Things are modular (users can select which Thing is relevant to their needs as well as the level of guidance they prefer: ‘Get started’, ‘Learn more’, and ‘Go deeper’) and customizable. While focusing on social science research that relies on quantitative data, it can be adapted for broader use in life sciences and other long tail small scale research relying on data analysis. See also https://curating4reproducibility.org/10things/

    Keywords Reproducibility · Curation · Open Data