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Data Science as a Research Support Service and the Role of the Libraries: UF's CNI Executive Roundtable Experience

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Data Science as a Research Support Service and the Role of the Libraries: UF's CNI Executive Roundtable Experience
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30
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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The objective of this project is to contribute to the Coalition for Networked Information (CNI) Executive Roundtable discussion on Data Science as a Research Support Service and the Role of the Libraries from 2:00 pm – 4:30 pm on March 16, 2022. The goal of the Executive Roundtable is to gain insights into how data science expertise is being provided to the university community in the broader context of research support services and the role of libraries at key CNI member institutions. Study design/methodology/approach: The project adopted a participatory worldview approach in collaboration with University of Florida (UF) Information Technology (IT) Research Computing Director, UF Clinical and Translational Science It Director, and UF Libraries to answer CNI’s ten (10) questions concerning data science as a research support and the role of libraries. Findings: The project revealed capacity, infrastructure, and resources socio-technical challenges that require collaboration across units to provide support, particularly human, skilled workforce, and financial circumstances. Originality/value: The project provided evidence from IT Research Computing and Clinical and Translational Science IT directors’ experiences and perspectives that contribute to developing data science as research support service and the Role of Libraries at the University of Florida. Research limitations/implications: The research limitations include lack of contributions from the College of Medicine, Institute of Food and Agricultural Sciences, and Engineering that represent among the top three academic units of research awards in 2021. Practical implications: Practical implications include collaboration between units to facilitate data science as a research support service across disciplines. Social implications: Social implications include enhanced awareness of other unit’s capacity, infrastructure, and resources for broader research support.
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