This is a 4-part class. Due to limited space, please only register if you can commit to all 4 sessions. When you register on the main event page, you will be registered for all 4 sessions.
*CE credit is only awarded after attending all 4 sessions.
As more and more datasets are collected, preserved, and shared in repositories, librarians should consider all of the factors involved in secondary data use for research. Such topics include how to search for existing data, how to assess the quality of a dataset and its appropriateness for the research study at hand, and how to work with data standards to enhance interoperability and discoverability. Teaching Secondary Data Use in Libraries is a four-part short course designed to share ideas around training students and researchers on finding and using existing datasets. Starting with a session on resources and tools available to find secondary data, this series will progress through teaching secondary data use, a discussion of data standards and interoperability, and a panel highlighting research projects using secondary data.
You can register for all 4 sessions on the main event page.
Dr. Adam Bouras, Senior Consultant and Adjunct Professor at Purdue University, will discuss the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) — what it is, why it is used, and what role librarians can play in data standardization.
By registering for this class, you are agreeing to the NNLM Code of Conduct
- Identify resources for finding secondary datasets.
- Describe effective approaches to teaching secondary data use.
- Determine appropriate applications for using generative AI in secondary data analysis.
- Design instruction for secondary data use that incorporates data standards and interoperability.
- Understand strengths and weaknesses of working with secondary data.