Getting practical with the FAIR Principles

About the Event Series

The Getting Practical with FAIR series, hosted by the NIH Office of Data Science Strategy (ODSS) and the GO FAIR Foundation, provides an opportunity to learn about the theoretical and practical foundations of the FAIR (Findable, Accessible, Interoperable, Reusable) Principles and how they can enhance the discovery, utility and attribution of biological and biomedical research data. The principles, first published in Nature in 2016, created a set of guidelines which seek to enhance the sharing and reuse of data. Through this event series, ODSS and the GO FAIR Foundation will support participants who seek to learn how FAIR works in practice, the skills needed to implement FAIR, and how to make FAIR a more routine aspect of their data management strategy.


Event 1: So, Why Go FAIR? 
April 17, 2023, 11:00 A.M.-12:00 P.M. EST

This interactive webinar will provide stakeholders with historical and technical context to better understand FAIR and how the principles might impact their work. Presenters will explore key issues around FAIR interpretation and implementation, and consider technological trends in the FAIRification and orchestration of research data. The event  is targeted towards a broad range of stakeholders including executives, policy makers, administrators, information technology experts, librarians, researchers, and data stewards. A few hands-on exercises will help to ground key concepts in practical examples. After the webinar, participants will:

  • Be aware of long-term trends to make data more machine-actionable.
  • Know what FAIR data are, and what they are not.
  • Be familiar with what it takes to go FAIR
  • Recognize the advantages of FAIR for the researcher and other stakeholders

A recording of this webinar is available here.

Event 2: Making Metadata FAIR 
June 12-13, 2023, 10:00 A.M.-2:00 P.M. EST

This second event in the “Getting Practical With The FAIR Principles” series will build on foundational familiarity with FAIR by providing participants with practical experience tackling a key challenge in FAIR implementation, creating FAIR metadata. Following an introduction to concrete strategies and tools, participants will collaborate on a set of guided exercises to generate FAIR metadata based on an example dataset. Through this hands-on approach, participants will gain experience addressing real-world social and technical challenges to make metadata FAIR. participants will leave the workshop with a better understanding of how FAIR works in practice, the skills needed to implement FAIR, and how to make FAIR a more routine aspect of their data management and/or stewardship practices.

Following the workshop, participants will be able to:

  • Define the characteristics of FAIR metadata
  • Describe the steps required to make metadata FAIR
  • Describe social and technical challenges related to creating FAIR metadata and strategies and tools that can help address them
  • Interact successfully with one or more technical tools for creating FAIR metadata

Register Now

This page last reviewed on May 15, 2023