Publications by authors named "Ariel Deardorff"

Objectives: To identify the engagement of health sciences librarians (HSLs) in open science (OS) through the delivery of library services, support, and programs for researchers.

Methods: We performed a scoping review guided by Arksey and O'Malley's framework and Joanna Briggs' Manual for Scoping Reviews. Our search methods consisted of searching five bibliographic databases (MEDLINE, Embase, CINAHL, LISTA, and Web of Science Core Collection), reference harvesting, and targeted website and journal searching.

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Introduction: As biomedical research becomes more data-intensive, computational reproducibility is a growing area of importance. Unfortunately, many biomedical researchers have not received formal computational training and often struggle to produce results that can be reproduced using the same data, code, and methods. Programming workshops can be a tool to teach new computational methods, but it is not always clear whether researchers are able to use their new skills to make their work more computationally reproducible.

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Objective: As computer programming becomes increasingly important in the biomedical sciences and more libraries offer programming classes, it is crucial for librarians to understand how researchers use programming in their work. The goal of this study was to understand why biomedical researchers who enrolled in a library-sponsored workshop wanted to learn to program in R and Python.

Methods: Semi-structured in-depth interviews were performed with fourteen researchers registered for beginning R and Python programming workshops at the University of California, San Francisco Library.

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Objective: To understand the experience of the informationist recipients of NLM-funded Administrative Supplements for Informationist Services and gather evidence for their impact on NIH-funded biomedical research.

Methods: A mixed methods approach consisting of a survey of principal investigators and a focus group of informationists.

Results: Informationists appeared to have a positive impact on their team's research, especially in the areas of data storage, data management planning, data organization, and literature searching.

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