- Olga Wodo (University at Buffalo)
- Brian Schuster (University of Texas at El Paso)
- Zachary Trautt (NIST)
- Logan Ward (Argonne National Lab)
- Kathryn Knight (GoFAIR US, ORNL)
- Arun Kumar Mannodi Kanakkithodi (Purdue University)
- Eric Toberer (Colorado School of Mines)
If you would like to join this working group then please contact one of the group members. Please open a discussion if you have a general question.
FAIR principles have been recognized as fundamental for exchanging scientific information. Communities within the materials science and engineering field have recognized the pressing need for such change in the research culture, as highlighted in the MGI 2021 document. FAIR principles have been recognized as critical to accelerating the change in how we produce, share, and reuse data. To fuel the cultural changes, the FAIR principles must be integrated into the material science and engineering curriculum. However, such a task may be daunting. To lower the entry barrier, this group aims to define (not implement) a small set of teaching modules that could be integrated into the materials science and engineering curriculum. The group is formed to outline the list of a few teaching modules with the goal of infusing the FAIR into the curriculum. Each teaching module description should include the aim, FAIR component/principle, and outcome and suggest the semester (or course) that such module could be integrated with.
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Organize core team and converge on an idea for initial set of modules and lessons.
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Launch formal working group, collect existing content, and author new content for modules and lessons.
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Test out content in academic and bootcamp setting
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Revise content based on trial run
- Develop an open-source and uniform set of resources to expand awareness and expertise in the FAIR Data Principles.
- Online resources to teach and learn FAIR Data Principles