Leveraging Data Communities to Advance Open Science: Findings from an Incubation Workshop Series

Ruediger, Dylan; MacDougall, Ruby; Cooper, Danielle; Carlson, Jake; Herndon, Joel; Johnston, Lisa

doi:10.18665/sr.317145

Cited by 5 publications

(4 citation statements)

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“…On the other hand, this study assumed that a larger staff would be an indicator of a repository's success. However, some researchers suggest a small repository staff working either with a supportive data community or backed by a larger team of reference/subject librarians can also be successful (Akers & Green, 2014;Bailey, 2005;Bell, Foster et al, 2005;Springer & Cooper, 2020;Ruediger et al, 2022). Finally, the analysis not supporting hypothesis eight was unsurprising, that the age of a repository would correlate with more depositors, confirming Tillman's (2017) findings that older repositories do not automatically have more depositors, although that might seem counter-intuitive on the surface.…”

Section: Discussionsupporting

confidence: 53%

Factors contributing to repository success in recruiting data deposits

Hayslett¹,

Jansen²

2022

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What factors make data repositories successful in recruiting research data deposits from scholars? While quite a few studies outline researchers’ data management needs and how repositories can meet those needs, few have assessed the success of various approaches. This study examines infrastructure for accepting data into repositories and identifies factors influential in recruiting data deposits.

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Section: Discussionsupporting

confidence: 53%

Factors contributing to repository success in recruiting data deposits

Hayslett¹,

Jansen²

2022

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“…“Successful data sharing ultimately depends on cultural and social infrastructures as much as on technical infrastructures” (Ruediger et al , 2022). A socio-technical system approach is needed to better understand organizational change programs and developing support services.…”

Section: Discussionmentioning

confidence: 99%

Leveraging socio-technical processes to support researchers

Smith

2023

DLP

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Purpose The purpose of this project was to develop research support services that address local and external research data management (RDM) support drivers within the existing organizational culture at the University of Florida. The goal was to prompt organization change to support a campus-wide electronic lab notebook. Design/methodology/approach This project used a mixed-methods research approach to cultivate an organizational change program that support technological infrastructure to benefit researchers. The mixed-methods research involved participation action research integrated with a stakeholder approach. Findings The development of the grant proposal which was unfunded led to development of continued project goals. This project confirmed the development for support for an institution-wide electronic research notebook (ERN) solution requires adherence to the summary of five key actions for developing RDM services. Failure to complete all of the key actions engenders fragmentation culture. Research limitations/implications This project includes implications for institutions to develop grant proposals with integrated budgets for research support services of funded projects; and to use the summary of key actions for developing RDM services articulated by Jones et al. (2013) in “How to Develop RDM Services – a guide for HEIs.” Both are need to support findable, accessible, interoperable and reusable data for researchers. Practical implications This project has practical implications for higher education institutions interested in leveraging socio-technical processes to advance the role of libraries as collaborator, partner and stakeholder in developing institution-wide adoption, support and training for ERN as a research support service to RDM. Social implications This paper contributes to the body of developing literature on ERN as support services to RDM lead by academic research libraries. Originality/value This project contributed to the change in organization culture resulting in the successful collaboration between the Research Office and College of Medicine to support an institution-wide ERN technological infrastructure for one year as a pilot at a large academic research institution in the southeast USA.

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“…Scholarly societies play a vital role in promoting and enabling data sharing and reuse among researchers (Maienschein et al, 2019;Ruediger et al, 2022). The Federation of American Societies for Experimental Biology (FASEB) recently launched DataWorks!…”

Section: Introductionmentioning

confidence: 99%

Establishing an Early Indicator for Data Sharing and Reuse

Piekniewska¹

2023

Preprint

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Funders, publishers, scholarly societies, universities, and other stakeholders need to be able to track the impact of programs and policies designed to advance data sharing and reuse. With the launch of the NIH data management and sharing policy in 2023, establishing a pre-policy baseline of sharing and reuse activity is critical for the biological and biomedical community. Toward this goal, we tested the utility of mentions of research resources, databases, and repositories (RDRs) as a proxy measurement of data sharing and reuse. We captured and processed text from methods sections of open access biological and biomedical research articles published in 2020 and 2021 and made available in PubMed Central. We used natural language processing to identify text strings to measure RDR mentions. In this article, we demonstrate our methodology, provide normalized baseline data sharing and reuse activity in this community, and highlight actions authors and publishers can take to encourage data sharing and reuse practices.

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Leveraging Data Communities to Advance Open Science: Findings from an Incubation Workshop Series

Cited by 5 publications

References 0 publications

Factors contributing to repository success in recruiting data deposits

Factors contributing to repository success in recruiting data deposits

Leveraging socio-technical processes to support researchers

Establishing an Early Indicator for Data Sharing and Reuse

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