Available Until 7/31/2024
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Research Data Management Training - On Demand*

For more information on this course, or to schedule, please contact the NNLM Training Office at nto@utah.edu.

This series is offered via Moodle.
Research Data Management On Demand is made up of four stand-alone classes that introduce principles and practices of research data management. There is no particular order or progression in which to take the classes. Expect to spend up to four hours on each class learning through tutorials, videos and hands-on activities.

The individual classes are:
1. Open Science and Data Science
2. Data Curation and Documentation
3. Data Security, Storage and Preservation
4. Data Sharing and Publishing

Course URL: https://nnlm.gov/training/class-catalog/research-data-management-training-demand

Course Objectives:

Through tutorials, videos and hands-on activities, participants will be able to:

Open Science and Data Science

    Articulate how open science supports research integrity and reproducibility.
    Describe the differences between research data management (RDM), data science, and open science
    Explore librarian roles to support data science

Data Curation and Documentation

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

Data Security, Storage and Preservation

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

Data Sharing and Publishing

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

Agenda:

Open Science & Data Science

  • Pre-test
  • Reading: The Open Science Training HandbookPage
  • Discussion: How open science helps researchers succeedForum
  • Lecture: NLM & NIH Partnership in Accelerating Discovery Through DataURL
  • Reading: Data Science: New Librarian Roles for a New Field of ResearchFile
  • Reading: Defining Data Librarianship: a Survey of Competencies, Skills, and TrainingFile
  • Post-test

Data Sharing and Publishing

  • Pre-test
  • Reading: Data Management Chapter 7Page
  • Reading: The FAIR Data PrinciplesPage
  • Complete: "NYU Compass Module 4"Page
  • Watch: BD2K Lecture "Why Data Sharing & Reuse Are Hard To Do?"Page
  • Assignment: FAIR Case Study
  • Post-test

Data Security, Storage and Preservation

  • Pre-test
  • View: DataONE Lesson 10Page
  • View: Regulatory Issues in Big Data for Genomics and Health OHSU BD2K Module 20Page
  • Discussion: Who owns the data?Forum
  • Complete: NYU Compass Module 7Page
  • Assignment: Gait Dynamics Database
  • Post-Test

Data Curation and Documentation

  • Pre-test
  • Reading: Data Management Chapters 3 & 6 (pg. 65-71)Page
  • View: NECDMC Module 2Page
  • Complete: NYU Compass Module 5Page
  • Assignment: Ocean Genome Legacy Case Study
  • Post-Test

MLA CE Credits: 4 (Per Class)