Examples
Worked examples
- Is an instance
A project DMP version 1.0 submitted at proposal, 2.0 updated mid-project, 3.0 finalised at closeout.
- Is an instance
A funder's monitoring system checking the DMP at each milestone.
Counter-examples
Looks similar, but isn't
- Not an instance
A one-off DMP PDF filed and never revisited (does not exercise the lifecycle).
- Not an instance
An institutional RDM policy (sets the lifecycle context, not a DMP itself).
Editorial commentary
The DMP lifecycle is the framing that stops a Data Management Plan (DMP) from being treated as a one-off proposal attachment. It names three phases a plan passes through over a project’s life: the creation phase at proposal stage, an active phase during project execution, and the closeout phase at or after project end. Each phase has a different primary audience (a funder reviewer at creation, the project team and data steward during the active phase, an auditor or future re-user at closeout) and a different relationship to truth: creation-phase content is intent (“we will…”), active-phase content is commitment being tracked, and closeout-phase content is evidence of what actually happened.
A research office typically encounters the lifecycle framing in three places: reviewing a draft DMP at proposal stage against a funder template, checking in on a DMP mid-project when a data steward flags a divergence from plan (a new sensitive dataset, a repository that fell through), and reconciling the DMP against actual deposits at project closeout for reporting or audit. Institutions that treat the DMP as a single static document tend to skip the middle step, which is exactly the gap that machine-actionable DMP (maDMP) tooling and the concept of an active DMP are designed to close.
How it differs from adjacent DMP concepts
- vs. DMP creation phase / DMP closeout phase — those are the individual phases; the lifecycle is the whole sequence and the transitions between them.
- vs. Living DMP — a living DMP is a specific implementation choice (versioned, citable) for moving through the lifecycle; not every DMP that passes through creation, active, and closeout phases is “living” in that stricter sense.
- vs. Static DMP — a static DMP nominally still has a lifecycle on paper, but in practice only the creation phase is ever populated; the active and closeout phases are never revisited.
References
- Simms, Jones, Mietchen & Miksa, “Ten principles for machine-actionable data management plans,” PLOS Computational Biology (2019).
Also known as
DMP phases
Machine-readable encodings
Use in your systems
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