Advancing Data Science, Data-Intensive Research, and Its Understanding Through Collaboration

Vitale, Cynthia Hudson; Kennedy, Mary Lee; Ruttenberg, Judy

doi:10.4018/978-1-7998-9702-6.ch002

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Consequently, the need for specialised support is scaling up as this framework also grows. Research libraries can provide an entry point for students who need to build their data science skills to participate fully as researchers in their field (Hudson Vitale et al, 2022).…”

Section: Introduction: Landscape Of Data Science Consulting and Need ...mentioning

confidence: 99%

The student staffing advantage: Data Science Consulting Service at NC State University Libraries

Marchesoni,

Freeman,

Tezbasaran

et al. 2024

Stat

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The primarily peer‐to‐peer, graduate student‐staffed Data Science Consulting Service at NC State University Libraries, within the Data & Visualization Services (DVS) department and collaborating closely with the Data Science Academy (DSA), has established a sustainable service and staffing model focused on providing broad data science analytic support to researchers across the university community. The service addresses the needs of university researchers who possess domain knowledge in their fields of study but a skills gap in the data science competencies required for research. The literature shows that it has been difficult for libraries to cover these needs with existing staffing models. Few universities follow the model practiced at NC State University, so a scan of the current landscape of data science consulting at universities across the country was performed to establish context. The support model and its advantages are described, including partnership with the DSA, student success, model sustainability and future directions for the service. Through a summary of the DVS assessment and needs evaluation process, the service's advantages in staying ahead of patron needs are illustrated. This scalable, sustainable, student‐focused model could be implemented by similar research institutions to expand the capacity of their technical research services.

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Section: Introduction: Landscape Of Data Science Consulting and Need ...mentioning

confidence: 99%

The student staffing advantage: Data Science Consulting Service at NC State University Libraries

Marchesoni,

Freeman,

Tezbasaran

et al. 2024

Stat

View full text Add to dashboard Cite

show abstract

“…The structures and service models can vary greatly in order to adapt to the possible structures and models that higher education institutions currently employ to address their respective approaches to data science (e.g., Herndon, 2021; Huebner et al, 2024). Recent national developments highlight the importance of data science across sectors and place increasing pressure on academic institutions to effectively engage in this landscape, which requires proficiency with data (Vitale et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Tell your story: Metrics of success for academic data science collaboration and consulting programs

Blake,

Griffith,

Pierce

et al. 2024

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Measuring success plays a central role in justifying and advocating for a statistical or data science consulting or collaboration program (SDSP) within an academic institution. We present several specific metrics to report to targeted audiences to tell the story for success of a robust and sustainable program. While gathering such metrics includes challenges, we discuss potential data sources and possible practices for SDSPs to inform their own approaches. Emphasizing essential metrics for reporting, we also share the metric gathering and reporting practices of two programs in greater detail. New or existing SDSPs should evaluate their local environments and tailor their practice to gathering, analysing and reporting success metrics accordingly. This approach provides a strong foundation to use success metrics to tell compelling stories about the SDSP and enhance program sustainability. The area of success metrics provides ample opportunity for future research projects that leverage qualitative methods and consider mechanisms for adapting to the changing landscape of data science.

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Advancing Data Science, Data-Intensive Research, and Its Understanding Through Collaboration

Cited by 2 publications

References 12 publications

The student staffing advantage: Data Science Consulting Service at NC State University Libraries

The student staffing advantage: Data Science Consulting Service at NC State University Libraries

Tell your story: Metrics of success for academic data science collaboration and consulting programs

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