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  • Research data management in practice: Results from a cross-sectional survey of health and medical researchers from an academic institution in Australia

    Author(s)
    Krahe, Michelle A
    Toohey, Julie
    Wolski, Malcolm
    Scuffham, Paul A
    Reilly, Sheena
    Griffith University Author(s)
    Wolski, Malcolm P.
    Scuffham, Paul A.
    Reilly, Sheena
    Krahe, Michelle
    Year published
    2020
    Metadata
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    Abstract
    Background: Building or acquiring research data management (RDM) capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that RDM practices influence the integrity and longevity of data, targeting RDM services and support in recognition of needs is especially valuable in health and medical research. Objective: This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia. Method: A cross-sectional survey was used to collect information from a convenience sample of 81 members of a research institute (68 ...
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    Background: Building or acquiring research data management (RDM) capacity is a major challenge for health and medical researchers and academic institutes alike. Considering that RDM practices influence the integrity and longevity of data, targeting RDM services and support in recognition of needs is especially valuable in health and medical research. Objective: This project sought to examine the current RDM practices of health and medical researchers from an academic institution in Australia. Method: A cross-sectional survey was used to collect information from a convenience sample of 81 members of a research institute (68 academic staff and 13 postgraduate students). A survey was constructed to assess selected data management tasks associated with the earlier stages of the research data life cycle. Results: Our study indicates that RDM tasks associated with creating, processing and analysis of data vary greatly among researchers and are likely influenced by their level of research experience and RDM practices within their immediate teams. Conclusion: Evaluating the data management practices of health and medical researchers, contextualised by tasks associated with the research data life cycle, is an effective way of shaping RDM services and support in this group. Implications: This study recognises that institutional strategies targeted at tasks associated with the creation, processing and analysis of data will strengthen researcher capacity, instil good research practice and, over time, improve health informatics and research data quality.
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    Journal Title
    Health Information Management Journal
    DOI
    https://doi.org/10.1177/1833358319831318
    Subject
    Health services and systems
    Public health
    Data management and data science
    Publication URI
    http://hdl.handle.net/10072/385998
    Collection
    • Journal articles

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