Enable machine readability
Machine readable data is data structured in a format that can be understood and processed by a computer. Some file formats, such as a PDF or Word documents, are human readable and easier to read and edit. This differs significantly from machine readable formats that can be processed by a computer and parsed or organized around specific information.
“Excel spreadsheets and CSV files, for example, have a “tabular” structure which computer programs can recognise and use, allowing you to easily add up columns of numbers, compute statistics, and so on. Other machine-readable formats such as XML documents and JSON files are much more flexible than spreadsheets” from http://community.openspending.org/research/handbook/machine-readable-data/
Dryad only includes 'data packages' but these contain a wide variety of 'data' types. The metadata (including DOI) is machine readable. The funder and rights information is important. Dryad has rights information with CC0 recommended, but I'm not sure funder information is widely provided by Dryad. Authors are encouraged to provide as much appropriate metadata as possible at submission, but there is also a curation process.
Zenodo record as an example: https://zenodo.org/record/7531
There you will see:
1) the link to the related publication (via its DOI)
2) the description field which is indexed and searchable (not sure if this is what you meant by "discovery layer”)
4) Minted DOI
5) Browse to Datasets and search only there
6) Several machine readable formats, including the DataCite link
7) Submitters can re-edit metadata, and curator can enrich
8) Harvested through OAI-PMH by several aggregators
Other important things demonstrated but not mentioned in your list are
+) The funder information
+) The rights information
Both of which are in the machine readable part as well
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