...
Dimension | Key notions |
FAIR data | Data, metadata, data products, cf existing models |
FAIR leadership | Types of leadership necessary for FAIR implementation |
FAIR strategyNow, the next FAIR stage and how to get there | Approaches to implement FAIR data principles, use and business cases |
FAIR roles | What kind of (human) roles are necessary for implementation of FAIR data principlesProcesses for FAIR to implement FAIR |
FAIR processes | Which processes must we explicitly implement |
FAIR knowledge | What needs to be known (by humans and machines) for FAIR implementation |
FAIR tools and infrastructures | From persistent identifiers to controlled vocabularies to semantic models |
Table - The
...
seven dimensions of the FAIR Maturity Matrix.
Combining all these factors is required to describe a given maturity level. It is also possible for organizations to reach various levels at a given point depending on the granularity (e.g. ecosystem/ enterprise/sector/department, etc.) considered. It is also possible for maturity to be not completely in sync for all dimensions. While FAIR implementation journeys may be similar, they are very context-dependent: the various dimensions intend to provide a broad frame to describe the situation accurately.
...
(Back to the FAIR Matrix).
...
FAIR processes
FAIR data principles implementation requires underlying processes connecting the necessary metadata, data, tools, roles and knowledge. Some of these processes may be implicit in the early stages of FAIR data implementation. Still, they will become more explicit and so ubiquitous that they will become transparent once we achieve the highest maturity levels.
...