diff --git a/DataManagementPlan.md b/DataManagementPlan.md new file mode 100644 index 0000000000000000000000000000000000000000..80c35336dcd80b6a37deab6d1cb63107296c67a0 --- /dev/null +++ b/DataManagementPlan.md @@ -0,0 +1,74 @@ +## Data Management Plan (DMP) + +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 + * IP: ownership, access rights, sharing rights, usage rights... + * What metadata format ? (refer to [Digital Curation Center a.k.a. DCC](http://www.dcc.ac.uk/) + * Interdisciplinary e.g. [Dublin Core](http://dublincore.org/metadata-basics/), disciplinary (SBML, EML, [CMDI](http://www.clarin.eu/content/component-metadata) + * Reference: [Standards and Metadata](http://www.inist.fr/formations/DMP-Standards-et-metadonnees/story_html5.html) + * Note: What about using the [Digital Object Identifier (DOI)](https://en.wikipedia.org/wiki/Digital_object_identifier)? + +### Data description + * Type of Data: source (refer above on data source), form, stability (static, incremental, substitutive), volumetry + * Which data formats? Opening (read), encoding (write), compression. + * How will you structure and name your folders and files? Naming conventions, folder structures (renaming tools exist) + * How will you ensure that different versions of a data set are easily identifiable? (version control) + * Reference: [Data description](http://www.inist.fr/formations/DMP-Description-des-donnees/story_html5.html) + +### Data sharing: immediate diffusion (focuses on direct and rich usage of data) + * Storage (commit/write): + * Which type of repository? (institutional, standard repository for the discipline...) + * Where (i.e. in which repository) will the data be deposited? + * Commit rights (who has the writing right access) + * Access (How will you make the data available to others?) + * Tools and means for retrieval and usage (software like data format readers, algorithms, analysis protocols...) + * [Digital Object Identifier (DOI)](https://en.wikipedia.org/wiki/Digital_object_identifier) + * Accessing rights (who can retrieve data, are they embargoes...) + * Usage (licenses: with whom will you share the data, and under what conditions?): + * access rights, mining rights, exploitation, reproduction, diffusion + * 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/) + * Reference: [Data sharing](http://www.inist.fr/formations/DMP-Partage-des-donnees/story_html5.html) + +### 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.