Biomedical & Health Research Data Management for Librarians*

 For more information or to schedule this course, please contact Jessi Van Der Volgen, nto@utah.edu.

Biomedical & Health Research Data Management for Librarians is a rigorous online training course, sponsored by the National Library of Medicine (NLM) and the National Network of Libraries of Medicine Training Office (NTO). This course provides basic knowledge and skills for librarians interested in helping patrons manage their research data. Attending this course will improve your ability to initiate or extend research data management (RDM) services at your institution.

The major goal of this course is to provide an introduction to data issues and policies in support of developing and implementing or enhancing RDM training and services at your institution. 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 management, choosing appropriate metadata descriptors or taxonomies for a dataset, addressing privacy and security issues with data, and creating data management plans.

In addition to improving your ability to add or enhance data management services or training at your institution, we hope that after completing this course, you will be part of the growing community of data librarians and contribute your knowledge and findings back to the field.

Course URL: https://news.nnlm.gov/nto/tag/rdm/ 


Learning Objectives:

Overall learning goal of the course: Increase skills and knowledge in order to develop or enhance Research Data Management training and services at students’ institutions.

Each module has specific objectives:
Module 1

  1. Describe how the data lifecycle fits into the larger research lifecycle
  2. Articulate the importance of RDM to the research lifecycle  
  3. Summarize the potential roles of librarians in RDM 

Module 2: 

  1. Explain what data curation encompasses
  2. Explain various types of data (e.g. surveys, video, images)
  3. Identify which data elements are important to document
  4. Recommend file naming convention based on best practices
  5. Check a dataset for potential privacy issues

Module 3: 

  1. Distinguish between standards, metadata, taxonomy, and ontology
  2. Locate and choose appropriate metadata/descriptors/ontologies for a given dataset
  3. Apply selected standards to a given dataset

Module 4

  1. Evaluate preservation needs of a dataset (e.g. file format, software)
  2. Identify appropriate data repositories for a given dataset
  3. Discuss potential solutions for datasets with security/privacy issues (HIPAA)
  4. Explain how policies affect data ownership, security, and storage

Module 5

  1. Articulate the FAIR data principles
  2. Explain the importance of research reproducibility
  3. Describe the concept of “open data” and challenges for sharing biomedical research data
  4. Explain data sharing incentives, data citations, and data journals

Module 6

  1. Explain DMP requirements of funding agencies (NIH, NSF)
  2. Create a DMP that meets the requirements of a selected funding agency

Each week of the online course includes readings, discussions, videos, tutorials, and a hands-on practical activity. 

Week 1: Data Lifecycle and RDM Overview

Week 2: Curation and Documentation

Week 3: Data Standards, Taxonomies, and Ontologies

Week 4: Data Security, Storage, and Preservation

Week 5: Data Sharing and Publishing

Week 6: Data Management Plans

MLA CE Credits: 32