This class is full
This online class meets the NLM/NIH strategic plan goal of accelerating discovery and advancing health through data driven research in order to increase health information access and use.
Keep reading to learn how to participate in this class.
The class is designed to provide information professionals working in health sciences with an introduction to research data management. The primary goal of this course is to improve your knowledge and skills in research data management and enable you to add or enhance research data management training and services at your institution.
This 9-week course will have participants read foundational texts in research data management, engage in discussions with other participants, complete assignments designed to improve knowledge and skills, and develop a final project of teaching a concept from the course or delivering a presentation on library roles in research data management.
Participants will work with course facilitators and community experts to complete course assignments and gain an understanding of the role of research data management in libraries.
Participation for this course is capped at 60 learners, so if you are interested in applying to register for this course, please commit to spending 3 total hours per week engaging with the course readings and assignments for the full 9 weeks of the course.
There will also be 10 community experts in the course to help learners. Please see below for more information on applying to be a community expert.
To be considered for enrollment as a learner in this course, please submit the following form by Sunday, January 14, 2024 at 11:59 p.m. Eastern Time:
https://www.nnlm.gov/form/ncds-fundamentals-of-health-scie
To be considered as a community expert to help learners in this course, please submit the following form by Sunday, January 14, 2024 at 11:59 p.m. Eastern Time:
Upon completion of the Fundamentals of Health Sciences Research Data Management, learners will be able to do the following:
- Explain different types (e.g., data curation, data preservation) and levels (e.g., linking to resources, consulting, and collaborative) of research data management services
- Describe tools, resources, and workflows to facilitate reproducibility and replicability
- Advise researchers in best practices for data management planning
- Explain how to effectively document and describe research data
- Advise how to safely store, protect, and share medical research data