Research Data Management On-Demand classes were active from July 7, 2022 through April 24, 2024.
4 free, 4-credit hour courses cover the five skill areas of the MLA Data Services Specialization (DSS) Basic Level. Explore topics such as open science and data science, data curation and documentation, data security, storage and preservation, and data sharing and publishing. These on-demand classes are offered in Moodle.
Objectives
See each individual class for learning objectives.
Class Length
4 hours
Continuing Education
This class qualifies for Medical Library Association (MLA) Data Services Specialization (DSS) Level 1.
How do you keep data secure and preserved? This introductory, four-hour, on-demand course uses readings, tutorials, videos, and hands-on scenarios to show how to evaluate preservation needs of a dataset, identify appropriate data repositories for a given dataset, examine security/privacy issues with data, and explain how data policies affect data ownership, security, and storage.
Learn about data curation in this introductory, four-hour, on-demand course, including the definition, types, and elements most important to document. You will also learn about file naming conventions and check a dataset for issues using a case study.
What is open science, and how does it differ from data science, and research data management? How can library staff support data science in their own work? This introductory, four-hour on-demand course introduces the concepts of open science, data science and research data management through readings, tutorials and videos. After taking this course, you will be able to describe the differences between research data management (RDM), data science, and open science, articulate how open science supports research integrity and reproducibility, and list ways librarian staff can support data science.
What are the FAIR data principles, and how do they relate to research reproducibility? This introductory, four-hour, on-demand course describes principles and challenges of data sharing, as well as data sharing incentives, open data, data citations, and data journals. Through readings, tutorials, videos, and hands-on scenarios you will increase your knowledge about data sharing and publishing.
This introductory, four-hour, on-demand course describes the definition, types, and elements of data curation that are most important to document in research data management. Through readings, tutorials, videos, and hands-on scenarios you will learn about types of data, which data elements are important to document, and best-practices for file naming conventions.
How do you keep data secure and preserved? This introductory, four-hour, on-demand course uses readings, tutorials, videos, and hands-on scenarios to show how to evaluate preservation needs of a dataset, identify appropriate data repositories for a given dataset, examine security/privacy issues with data, and explain how data policies affect data ownership, security, and storage.
What are the FAIR data principles, and how do they relate to research reproducibility? This introductory, four-hour, on-demand course describes principles and challenges of data sharing, as well as data sharing incentives, open data, data citations, and data journals. Through readings, tutorials, videos, and hands-on scenarios you will increase your knowledge about data sharing and publishing.
What is open science, and how does it differ from data science, and research data management? How can library staff support data science in their own work? This introductory, four-hour on-demand course introduces the concepts of open science, data science and research data management through readings, tutorials and videos. After taking this course, you will be able to describe the differences between research data management (RDM), data science, and open science, articulate how open science supports research integrity and reproducibility, and list ways librarian staff can support data science.
