Add machine actionability with use of IDs and clarify scope of maDMP standard for data management issues

[laihokau]

This is a summary of comments arising from OSTrails National pilot in Finland:

General, use of ID and DOs should be increased in the standard, and re-assess how to reduce string fields utilizing more structural design, nested data structure, controlled lists and vocabularies.

Add ID for both organization of PI and contributors, use ROR or other id: e.g. organization_pi,
organization_contributor

Define scientific discipline of project e.g. project_discipline following by UNESCO classification.

To make DMP alive define next review date e.g. nextreview_dmp to remind researcher to update the DMP e.g. following requirement from funder or home organization.

We should limit information asked in DMP about datasets to be published and their metadata. Suggested to remove the following fields: distribution_dataset, issued_dataset, keyword_dataset, language_dataset and metadata_dataset
These are about publishing and metadata, not about data management. If someone needs to combine DMP and CRIS, this information needs to be interoperable, but this should NOT be part of DMP.

Add estimate_datasize to give a rough estimate of the size of the data produced and/or collected.

Define clear attributes for the data life cycle from reuse, sharing active data, managing backups and versions, publishing, deletion, and archiving.

Design how to manage complexity of research project, and multiple grant decisions to reduce burden from researchers and avoid requiring grant specific DMPs.

Consider benefits for the researcher of adding "Rights related to data fields" e.g.
ownership_data_right: Who owns the data/rights related to the data?
IPR_copyright: Are there IPR or copyright issues?
Agreements: Are there any agreements related to the rights to the material?