What does this research mean for the field?

A large language model (LLM) can effectively prefill a Data Management Plan (DMP) using input from a research proposal. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to explore how a large language model (LLM) can assist in pre-filling data management plans (DMPs) using research proposals as input.

February 27, 2026Open Access

GenAI for Research Support: a case to DMPs pre-filling

Key Points

The aim is to explore how a large language model (LLM) can assist in pre-filling data management plans (DMPs) using research proposals as input.
Delivered a presentation at the International Digital Curation Conference 2026.
Utilized a large language model (LLM) to pre-fill DMPs.
Collected feedback from researchers at TU/e on the effectiveness of the LLM.
Demonstrated the capability of the LLM to efficiently compile DMPs.
Received positive feedback regarding the LLM's effectiveness in aiding the DMP compilation process.

Abstract

Presentation delivered at the International Digital Curation Conference 2026 (Zagreb 16-18 February 2026) organised by the Digital Curation Centre. It shows how a LLM can be used to prefill a DMP having as input a research proposal, and it includes the feedback from TU/e researchers that used the LLM and evaluated its effectiveness in compiling the DMP.

GenAI for Research Support: a case to DMPs pre-filling

Key Points

Abstract

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