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The coursebook link: maastrichtu-library.github.io/FAIR-research-data-coursebook/ About 📗 Usually, training materials on FAIR principles are tedious and contain extensive theory. In this Library Carpentries-based coursebook, we aim to teach the implementation of FAIR principles differently. It has low entry-level materials and examples that the average researcher can understand and immediately apply. Some relevant topics the coursebook aims to address are the following: Get to know the importance of a “Research Digital Object”. Explore the available open-source tools for interoperability to make research digital objects sustainable. You will learn what “Data Terms of Use” and “Data Access Protocols” are and how to create them. You will review the differences and similarities of “Data Descriptions” in different science fields to discuss what we can do (as a scientific community) to standardize these practices. You will learn what “Rich Metadata” technically means on the Semantic Web and its relation to sustainable research output for future researchers. 💡 Following a bolder approach, we want to teach the implementation of FAIR principles differently. There is less focus on the theory and more emphasis on examples. Guided by 6 steps in Research Data Management
The coursebook is found at the following link: https://maastrichtu-library.github.io/FAIR-research-data-coursebook/
Bootcamp, Research Data Management, Research Data Reuse, FAIR Digital Objects, FAIR
Bootcamp, Research Data Management, Research Data Reuse, FAIR Digital Objects, FAIR
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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