The many levels of data management maturity

After managing scientific data sets for many years, I have taken a little time to reflect on the maturity and rigour with which these data are managed by various organisations that I have interacted with.

To this end I wish to suggest a 4 part scale for the so called 'maturity' of data management. I hope this helps those tasked with data management think about where they are in their evolution or journey.

Thoughts and comments welcome.

[Level 0] No use of controlled vocabularies or other data standards.

The wild west of data management.

[Level 1] Full and appropriate adoption of controlled vocabularies.

Master data recognised and used.

https://en.wikipedia.org/wiki/Controlled_vocabulary

[Level 2] Full and appropriate use of relevant ontologies.

Master data recognised and uses relationships between data terms.

https://en.wikipedia.org/wiki/Ontology

[Level 3] Full and appropriate adoption of minimum information standards.

A relevant blend of ontologies for each application domain.

https://en.wikipedia.org/wiki/Minimum_information_standard

[Level 4] Full and appropriate adoption of FAIR data principles.

Well described data and metadata that is able to be found, accessed, integrated or reused.

https://en.wikipedia.org/wiki/FAIR_data