Innovation & Research Practice

Paper: Program Description Abstract

Designing and Teaching a Hands-on Reproducibility Workshop in REDCap and R

Tuesday, May 7
4:50 PM - 5:05 PM
Room: Columbus EF (East Tower, Ballroom/Gold Level)

Background : In recent years, there has been increased scrutiny on issues of scientific reproducibility. In 2016, NIH began requiring that grant applications address rigor and reproducibility. Issues of reproducibility arise across the data lifecycle, from collecting to processing to analyzing data. Our library provides lectures on rigor and reproducibility to graduate students, and hands-on training for faculty, students, and research staff in REDCap and R. We saw an opportunity to integrate the hands-on tools-based training into a framework that emphasized issues of reproducibility and highlighted how to use those tools to maximize reproducibility throughout data collection, processing, and analysis.

Description : We developed a full-day reproducibility workshop. Lectures covered clinical research data management taught by a librarian and an introduction to recommended practices for reproducibility taught by a senior data analyst from the Department of Population Health. Hands-on training, taught by librarians, covered REDCap and R. We created two datasets to use for hands-on exercises: clinical study data in REDCap, and EHR data that included data from the REDCap study “participants”. The class covered: 1) best practices in collecting, processing, and analyzing data including best practices in scientific computing, 2) using REDCap’s online designer, shared libraries, and data dictionary feature to create data collection instruments that facilitate reproducibility, and 3) basics of R including the tidyverse packages and R Markdown. The class concluded with a case study using R Markdown to reproducibly process and analyze the simulated REDCap and EHR data.

Conclusion : Eighteen people attended the workshop (55 registrations including waitlist), including faculty, students, and staff. Workshop evaluations were positive (94% would recommend workshop, 94% would use what they learned). However, five students indicated the R instruction was too advanced, and others suggested decoupling the topics or allowing more time for the material. Library instructors concluded that modifications were warranted before offering the workshop again. Issues to consider ranged from the technical -- finding ways to streamline the somewhat time-consuming and error-prone set-up process -- to broader questions such as whether there was value in linking REDCap and R in this way.

Alisa Surkis

Assistant Director, Research Data and Metrics/Vice Chair for Research
NYU Health Sciences Library
New York, New York

Alisa Surkis, PhD, MLS is the Assistant Director for Research Data and Metrics and the Vice Chair for Research at the NYU Health Sciences Library. She serves as a co-Director for Team Science and leads the Workforce Data Capacity Core within the Biomedical Informatics Program for the NYU Clincical and Translational Science Institute. She is the Data Science Core Director for an NIH BRAIN Initiative funded project on Oxytocin Modulation of Neural Circuit Function and Behavior.

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Fred LaPolla

Research and Data Librarian
NYU Health Sciences Library
New York, New York

Fred LaPolla is a Research and Data Librarian at NYU Health Sciences Library. He works with NYU's Data Services team providng data visualization workshops and is liaison to NYU Langone Health's Departments of General Internal Medicine and Radiology. He has been with NYU HSL since 2015 and earned his MLS at Queens College, CUNY. He is also interested in cooking and drawing.

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Kevin Read

Lead, Data Discovery and Data Services Librarian
NYU Health Sciences Library
New York, New York

Kevin Read, MLIS, MAS is the Lead of Data Discovery and Data Services Librarian at NYU Langone Health. He leads the NYU Data Catalog project; an initiative to make research datasets created and used by NYU researchers more discoverable. He also leads the Data Catalog Collaboration Project, a multi-site collaboration consisting of eight academic institutions working to improve the discoverability of institutional research data using the NYU Data Catalog model.

Beyond his data discovery efforts, Kevin provides training and research support to faculty, residents, students and staff on topics including: clinical research data management, REDCap, reproducibility, and data sharing.

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Mark Butler

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Nicole Contaxis

Data Catalog Coordinator
NYU Health Sciences Library
New York, New York

Nicole Contaxis, MLIS, is the NYU Data Catalog Coordinator at the NYU Health Sciences Library. She works alongside researchers to make research data discoverable. Her main responsibilities include planning and conducting outreach events, curating metadata in the catalog, and collaborating with other medical librarians through the Data Catalog Collaboration Project. Her areas of interest include data sharing, data ethics, and community engagement. She received her MLIS degree from UCLA and is currently pursuing an MA in Bioethics at NYU.

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