Data management plans
A DMP answers, before the data exists, the questions that hurt
when answered too late: what data will the project produce, where
will it live, who may see it, what does that cost, and what
survives the grant. Funders require one with most proposals; the
useful version is not the compliance document but the honest
operating plan - and because it describes practices this pack
already engineers, most of a good DMP can be drafted from, and
checked against, the project itself. The software counterpart
(rseng-management-planning's SMP practice) shares this design; write the two
consistently and cross-reference them.
What a plan covers
The standard sections, each answered from project reality:
- Data description: types, formats, expected volumes, sources -
name open formats deliberately (rseng-scientific-file-formats)
and reused third-party datasets with their licenses and terms.
- Documentation and metadata: data dictionaries, READMEs,
community metadata standards for the domain
(rseng-data-management owns the practice; the DMP states which).
- Storage and backup during the project: where working data
lives, replication, who administers it - institutional storage
beats lab improvisation; sensitive data goes where the
steward says (rseng-regulatory-compliance).
- Access, sharing and legal: who can access what and when, embargo
plans, consent and GDPR constraints, anonymization strategy -
with honest limits stated (rseng-regulatory-compliance); "as open
as possible, as closed as necessary" is the working frame.
- Preservation and sharing after the project: which data is
deposited, where (domain repository first, Zenodo-class
otherwise - rseng-archiving), with what identifiers and licenses
(rseng-licensing for data licenses), and what is deliberately
discarded (retention has costs; keeping everything is not a
plan).
- Responsibilities and resources: named roles (who curates, who
deposits), storage and curation costs as budget lines - data
work is fundable work; say so in the proposal.
Proportionality: a simulation project with regenerable outputs
needs a lean DMP centered on code and configs
(rseng-reproducibility); a project collecting human-subject data
needs the full treatment. Match depth honestly.
Machine-actionable DMPs
DMPs are becoming structured data, not prose PDFs:
- The RDA DMP Common Standard defines the maDMP schema - a JSON
model of datasets, distributions, hosts, licenses and costs
that tools exchange.
- The Data Stewardship Wizard (DS-Wizard) builds DMPs from
questionnaire knowledge models and exports funder formats plus
maDMP JSON; DMPonline carries the major funder templates.
When the user's institution runs one of these, draft THERE (or
produce content ready to paste), so the plan lands in the
system reviewers and stewards actually use.
- The agent-friendly consequence: a structured DMP is checkable -
datasets listed in the plan can be diffed against datasets the
project actually has, licenses in the plan against LICENSE
files, deposit promises against archive records
(rseng-archiving).
The DMP as a living document
Plans drift: new instruments, bigger volumes, a dataset that
cannot be shared after all. Treat the DMP like the SMP:
- Version it with the project (repository or the DMP platform's
versioning); update at milestones, reporting deadlines and
whenever data reality changes - a plan contradicted by practice
is a liability at review and audit time
(rseng-management-planning owns the cadence).
- Run a drift check when revisiting: promised repositories vs
actual deposits, promised metadata vs delivered, promised
retention vs disk reality. Report gaps as actions with owners.
- Record AI assistance in drafting or revising the plan in
aidecl.yaml (rseng-ai-declaration).
Working with this skill
This skill is source-independent: its authority is the RDA common
standard, the platform documentation and the RDMkit guidance
linked below. It is the data twin of
the SMP practice in rseng-management-planning; rseng-data-management holds the
underlying practice.
Learn more (verified):
Related skills
Check whether any of these applies before moving on:
- rseng-archiving - deposit and preservation promises
- rseng-data-management - the practice the plan describes
- rseng-licensing - data license choices in the plan
- rseng-management-planning - SMP twin, shared drafting cadence
- rseng-regulatory-compliance - GDPR, consent and anonymization sections
- rseng-scientific-file-formats - naming open formats deliberately
1---2name: rseng-data-management-plans3description: Covers data management plans (DMPs) for research projects: what funders require, drafting a DMP from the project's actual data reality (types, volumes, storage, sharing, preservation, responsibilities, costs), machine-actionable DMPs (RDA common standard, Data Stewardship Wizard, DMPonline funder templates), and keeping the plan synchronized with practice. Use when a proposal or project needs a DMP, when the user mentions data management plans, maDMPs, DS-Wizard or DMPonline, when funder or institutional data policy applies, or when the existing DMP has drifted from what the project actually does with its data. (Day-to-day data practice is rseng-data-management; the software management plan twin is rseng-management-planning.)4license: CC-BY-4.05---67# Data management plans89A DMP answers, before the data exists, the questions that hurt10when answered too late: what data will the project produce, where11will it live, who may see it, what does that cost, and what12survives the grant. Funders require one with most proposals; the13useful version is not the compliance document but the honest14operating plan - and because it describes practices this pack15already engineers, most of a good DMP can be drafted from, and16checked against, the project itself. The software counterpart17(rseng-management-planning's SMP practice) shares this design; write the two18consistently and cross-reference them.1920## What a plan covers2122The standard sections, each answered from project reality:23241. Data description: types, formats, expected volumes, sources -25 name open formats deliberately (rseng-scientific-file-formats)26 and reused third-party datasets with their licenses and terms.272. Documentation and metadata: data dictionaries, READMEs,28 community metadata standards for the domain29 (rseng-data-management owns the practice; the DMP states which).303. Storage and backup during the project: where working data31 lives, replication, who administers it - institutional storage32 beats lab improvisation; sensitive data goes where the33 steward says (rseng-regulatory-compliance).344. Access, sharing and legal: who can access what and when, embargo35 plans, consent and GDPR constraints, anonymization strategy -36 with honest limits stated (rseng-regulatory-compliance); "as open37 as possible, as closed as necessary" is the working frame.385. Preservation and sharing after the project: which data is39 deposited, where (domain repository first, Zenodo-class40 otherwise - rseng-archiving), with what identifiers and licenses41 (rseng-licensing for data licenses), and what is deliberately42 discarded (retention has costs; keeping everything is not a43 plan).446. Responsibilities and resources: named roles (who curates, who45 deposits), storage and curation costs as budget lines - data46 work is fundable work; say so in the proposal.4748Proportionality: a simulation project with regenerable outputs49needs a lean DMP centered on code and configs50(rseng-reproducibility); a project collecting human-subject data51needs the full treatment. Match depth honestly.5253## Machine-actionable DMPs5455DMPs are becoming structured data, not prose PDFs:5657- The RDA DMP Common Standard defines the maDMP schema - a JSON58 model of datasets, distributions, hosts, licenses and costs59 that tools exchange.60- The Data Stewardship Wizard (DS-Wizard) builds DMPs from61 questionnaire knowledge models and exports funder formats plus62 maDMP JSON; DMPonline carries the major funder templates.63 When the user's institution runs one of these, draft THERE (or64 produce content ready to paste), so the plan lands in the65 system reviewers and stewards actually use.66- The agent-friendly consequence: a structured DMP is checkable -67 datasets listed in the plan can be diffed against datasets the68 project actually has, licenses in the plan against LICENSE69 files, deposit promises against archive records70 (rseng-archiving).7172## The DMP as a living document7374Plans drift: new instruments, bigger volumes, a dataset that75cannot be shared after all. Treat the DMP like the SMP:7677- Version it with the project (repository or the DMP platform's78 versioning); update at milestones, reporting deadlines and79 whenever data reality changes - a plan contradicted by practice80 is a liability at review and audit time81 (rseng-management-planning owns the cadence).82- Run a drift check when revisiting: promised repositories vs83 actual deposits, promised metadata vs delivered, promised84 retention vs disk reality. Report gaps as actions with owners.85- Record AI assistance in drafting or revising the plan in86 aidecl.yaml (rseng-ai-declaration).8788## Working with this skill8990This skill is source-independent: its authority is the RDA common91standard, the platform documentation and the RDMkit guidance92linked below. It is the data twin of93the SMP practice in rseng-management-planning; rseng-data-management holds the94underlying practice.9596Learn more (verified):97 - https://rdmkit.elixir-europe.org/data_management_plan - RDMkit98 on data management plans99 - https://github.com/RDA-DMP-Common/RDA-DMP-Common-Standard -100 RDA maDMP common standard101 - https://ds-wizard.org - Data Stewardship Wizard102 - https://dmponline.dcc.ac.uk - DMPonline funder templates103104<!-- related-skills:begin -->105106## Related skills107108Check whether any of these applies before moving on:109110- rseng-archiving - deposit and preservation promises111- rseng-data-management - the practice the plan describes112- rseng-licensing - data license choices in the plan113- rseng-management-planning - SMP twin, shared drafting cadence114- rseng-regulatory-compliance - GDPR, consent and anonymization sections115- rseng-scientific-file-formats - naming open formats deliberately116117<!-- related-skills:end -->