
FAIR data is not only becoming a requirement set by European and national funding agencies, but by making your data FAIR, you are making it easier for others to find, use, and cite your data. In this course you will learn how to make your data Findable to a wide audience, how to make them Accessible to people and to machines, and how to make them Interoperable so they can be Reused by others. After learning the principles, you will practice your knowledge in quizzes and practical sessions. This is a 3-day course for onsite participants, of which the first 2.5-days are also open to online participants. In the final half day, the onsite students will bring all they have learned together in an interactive Make-My-Data-FAIR session. We will also have a "Data Clinic" in which the onsite students can ask their particular questions of the various experts of the VLIZ Data Centre on data FAIRness, data management, data archiving, etc.
Data Access, Research communities, Data steward, Level Basic, Research manager, Students, Data Discovery, Data Scientist, Generic, Data Management, FAIR
Data Access, Research communities, Data steward, Level Basic, Research manager, Students, Data Discovery, Data Scientist, Generic, Data Management, 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 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| 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 |
