Best AI tools for writing a data management plan (researcher)

4 tools selected and reviewed

The data management plan has become mandatory for most French and European public funding, with the ANR requiring it within six months of the project start. It is an administrative document nobody was taught to write: you have to describe the data produced, its format, its storage, how long it is kept, the conditions for sharing it and the legal questions attached to it.

We kept the tools that help produce a structured document and retrieve the exact requirements of the funder, without ever replacing a check with your research support office.

Our quick recommendation

1Highest rated
ClaudeProductivity & assistants

Anthropic's AI assistant, excellent at writing and document analysis.

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2Excellent choice
NotebookLMPresentations & documents

Analyze and synthesize your documents with Google's AI

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3Worth a look
ChatGPTWriting & content

The versatile AI assistant for writing, summarizing, and brainstorming.

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All results

4 tools
ToolBest forPriceFRLevelVerdictRating
ClaudeAnthropic's AI assistant, excellent at writing and document analysis.Freemium🇫🇷BeginnerExcellent★ 4.8
NotebookLMAnalyze and synthesize your documents with Google's AIFreemium🇫🇷BeginnerVery good★ 4.5
ChatGPTThe versatile AI assistant for writing, summarizing, and brainstorming.Freemium🇫🇷BeginnerExcellent★ 4.8
PerplexityThe AI search engine that answers with sources cited.Freemium🇫🇷BeginnerVery good★ 4.6

Frequently asked questions

What is a data management plan and who requires one?

It is a document describing the life cycle of a project's data: what is produced, in what format, where it is stored, who can access it, what is shared and when. The ANR requires one for the projects it funds, Horizon Europe does too, and a growing number of institutions ask for one outside any funding. It is a living document, updated as the project runs.

What do the FAIR principles mean in a data management plan?

FAIR stands for findable, accessible, interoperable and reusable. In practice the funder expects concrete answers: a persistent identifier for the dataset, a repository that distributes it, an open rather than proprietary format, and an explicit reuse licence. An AI can help you phrase those answers, it cannot choose the repository for you.

How should personal data be handled in a data management plan?

By distinguishing anonymisation from pseudonymisation, because the two do not carry the same legal consequences: pseudonymised data remains personal data under the GDPR, with the obligations that follow. This part of the plan is written with your institution's data protection officer, not alone with an assistant.

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