rseng-data-management-plans

Solid

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.)

Data & Documents 14 stars 2 forks Updated 4 days ago MIT

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Quality Score: 83/100

Stars 20%
39
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# 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: 1. 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. 2. Documentation and metadata: data dictionaries, READMEs, community metadata standards for the domain (rseng-data-management owns the practice; the DMP states which). 3. 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). 4. Access, sharing and legal: who can access what and when, embargo plans, consent and GDPR constraints, anonymization strategy - with honest limits stated (rseng-r...

Details

Author
fdiblen
Repository
fdiblen/rseng-agent-skills
Created
4 days ago
Last Updated
4 days ago
Language
Python
License
MIT

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