This document summarizes the various fields that are most often encountered within a [Data Management Plan](https://en.wikipedia.org/wiki/Data_management_plan)(DMP).
### Dataset reference and name
### Data set name and high level description
### Standards and Metadata: Data origin and content
* How will the data be obtained? (created or collected among existing data)
* Can any of this information be created automatically?
* What metadata content standards will you use and why?
* Intellectual content: title, summary, domain, keywords, resource type
* Production content: date, creator (affiliation), project (goal), financing bodies, production means (where, acquisition/production instrument) What standards or methodologies will you use for obtaining them? (e.g. when collecting describe from which source, with which filters, cleanup methods...)
* Technical characteristics: format, volumetry, files, structure/organisation
* Can be dealt with [Creative Commons](https://creativecommons.org) licenses like [CCO](https://creativecommons.org/publicdomain/zero/1.0/) or [CC BY](http://creativecommons.org/licenses/by/4.0/)
### Archiving and preservation: focuses on mid to long term access (storage and backup)
* What is the long-term preservation plan for the dataset? e.g. deposit in a data repository
* Will additional resources be needed to prepare data for deposit or meet charges from data repositories?
* Is additional specialist expertise (or training for existing staff) required?
* Do you have sufficient storage and equipment or do you need to cost in more?
* Will charges be applied by data repositories?
* Have you costed in time and effort to prepare the data for sharing / preservation?
* Notes:
* In France [CINES'](https://www.cines.fr/) vocation is to offer archiving services
* Standards: METS (Metadata Encoding and Transmission Standard) and PREMIS (Preservation metadata: implementation strategies)
* Data repositories are usually concerned with diffusion but not with archiving
*[OAIS (Open Archival Information System)](https://en.wikipedia.org/wiki/Open_Archival_Information_System) normalizes (ISO) the archival systems and [describes](https://en.wikipedia.org/wiki/Open_Archival_Information_System#/media/File:OAIS-.gif): ingestion (input to the system), access (outputs of the system), management, storage...
* Reference: [Archiving and preservation](http://www.inist.fr/formations/DMP-Archivage-des-donnees/story_html5.html)
### Data discoverability
* Are the data and associated software produced and/or used in the project discoverable (and readily located), identifiable by means of a standard identification mechanism (e.g. Digital Object Identifier)?
* How will potential users find out about your data?
* Will you provide metadata online to aid discovery and reuse?
### Data accessibility
Are the data and associated software produced and/or used in the project accessible and in what modalities, scope, licenses?
### Data assessability and intelligibility
Are the data and associated software produced and/or used in the project assessable for and intelligible to third parties in contexts such as scientific scrutiny and peer review?
### Reusability
Are the data and associated software produced and/or used in the project useable by third parties even long time after the collection of the data?
### Interoperability to specific quality standards
Are the data and associated software produced and/or used in the project interoperable allowing data exchange between researchers, institutions, organizations, countries, etc?
### Sources
Content of this document was manually extracted from [DMPOnline tool](https://dmponline.dcc.ac.uk).
Note that doing taking into account the [DMPTool](https://dmptool.org/) site content proved to be harder since DMPTool is customized with disciplinary (scientific domain) oriented DMP templates.
