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Applications Open for RDM 102: Beyond Research Data Management for Biomedical and Health Sciences Librarians

Posted in: Blog, Classes, Online Classes

updated 11/29/2018

Course Description

Biomedical and health sciences librarians are invited to participate as students or mentors in a rigorous online training course going beyond the basics of research data management, sponsored by the National Library of Medicine (NLM) and the National Network of Libraries of Medicine Training Office (NTO). This course will expand on concepts covered in RDM 101: Biomedical and Health Research Data Management Training for Librarians, and threaded throughout will be the librarian’s role in research reproducibility and research integrity. It will also include practice in using Jupyter notebooks through an open-source browser-based application (jupyterhub) that allows users to create and share documents that contain live code, equations, visualizations, and narrative text.

The major aim of this course is to provide an introduction to the support of data science and open science with the goal of developing and implementing or enhancing data science training and services at participants’ institutions. This material is essential for decision-making and implementation of these programs, particularly instructional and reference services. The course topics include an overview of data science and open science, data literacy, data wrangling, data visualization, and leadership.

The online asynchronous component of the program is 6 weeks from February 20 – April 5, including a catch-up week, and then followed by a synchronous online session during the week of April 8. The format includes video lectures, readings, case studies, hands-on exercises, and peer discussions. There will be optional weekly office hours. Under the guidance of a mentor, participants will complete a Final Project to demonstrate improved skills, knowledge, and ability to support data science services at their institution. Expect to spend about 6 hours each week on coursework and the project.

Mentors will assume the role of a researcher with a dataset seeking data services support. They will work with groups of 4-5 mentees. Before the course, mentors will select a dataset and scope research questions to form the basis for mentee projects. During the course, mentors will participate in class discussions, sharing expertise as needed, and meet with mentees (individually or as a group) to provide guidance in the completion of the project. For example, during the data visualization module, mentors may provide guidance in using software, choosing appropriate chart types, etc. At the end of the course, mentors must be available for a synchronous online session during the week of April 8 where mentees will present their findings, and will provide written project feedback to each mentee.


  • Shirley Zhao, MSLIS, MS, Data Science Librarian, Spencer S. Eccles Health Sciences Library, University of Utah
  • Leah Honor, MLIS, Education & Clinical Services Librarian, Lamar Soutter Library, University of Massachusetts Medical School
  • Tess Grynoch, MLIS, Research Data & Scholarly Communications Librarian, Lamar Soutter Library, University of Massachusetts Medical School
  • Margaret Henderson, MLIS, Health Sciences Librarian, San Diego State University

Important Dates

  • Application deadline: January 4, 2019
  • Notifications begin: January 14, 2019
  • Course: February 20 – April 12, 2019

For Student Applications

Applicants must have previous training or experience in research data management through the RDM 101 course or attest to the learning objectives listed here. Applications are open to health science information professionals working in libraries located in the US; or with permission of the instructors, persons living outside the US with LIS training and wishing to obtain a position in a US based library. A letter of institutional support may be required (see application instructions below). Enrollment is limited to 40.

CE Credits
Students who complete all modules, the Final Project, and the course evaluation will receive MLA CE credit (exact number of hours to be determined). No partial CE credit is granted.

What does it cost?
There is no charge for participating in the program.

Application Instructions
Please fill out the online application form, and upload PDFs of your current CV and your letter of institutional support (if applicable) by January 4, 2019: https://redcap.iths.org/surveys/?s=7LER8MMRCJ

If you did not complete either the Spring 2018 or Fall 2018 RDM 101 courses or if you did but changed employers, a letter of institutional support must come from your current supervisor and address time for participation in this online course. If you are not currently employed, you may seek a letter from 1) a previous employer who can speak to your qualifications, accomplishments, and commitment; or 2) your Regional Medical Library.

For Mentor Applications

We are seeking 8 experienced data librarians (not necessarily in health sciences) to participate in this program as mentors to support students completing individual projects, which are designed to apply skills acquired each week. Mentors should be familiar or have experience with the topics of the course. Ideally, mentors will also have experience using Jupyter notebooks, Open Refine, GitHub, and basic programming in Python or R.


  1. Dataset and potential research questions
  2. Log of mentor/mentee interactions
  3. Written feedback to each mentee
  4. Summary report of experience as mentor, including suggestions for course.

Mentors will be compensated $1000 for their time and required to submit a W-9 and a contract with the University of Utah.

Application Instructions
Please fill out the online application form, and upload a PDF of your current CV by January 4, 2019: https://redcap.iths.org/surveys/?s=ACPRDF48KX


Please contact NTO or Shirley Zhao, RDM Project Lead and Training Development Specialist.

Developed resources reported in this site are supported by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM012344 with the University of Utah Spencer S. Eccles Health Sciences Library. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH.

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