A Vision for Data Management Plans in the NFDI

A new publication discusses possible future roles of Data Management Plans (DMPs), templates, and tools in the upcoming NFDI service architecture. This position paper summarises ideas developed and collected during interdisciplinary workshops of the Data Management Planning Working Group (infra-dmp), which is part of the section Common Infrastructures of the National Research Data Infrastructure (NFDI) in Germany.

At present, data management plans (DMPs) are still often perceived as documents with the main purpose of satisfying requirements of funding agencies on how research data will be handled during a funded project. During the project, it is still common for them to not be actively employed in the processes.

The overall goal of the infra-dmp is the consolidation of existing DMP approaches across all consortia to establish a common understanding and standards for DMPs in the NFDI. It’s important to note that the information structurally stored in a DMP has the potential to be used to embed the DMP in a practicable operational concept that combines project and data management as well as documentation and report functions. For this reason, it is important to move away from viewing DMPs solely from the perspective of a supplement to grant proposals and to consider other stakeholder groups and communities with their specific workflows beyond pure research processes.

The position paper presents infra-dmp’s vision of a possible future role of DMPs, templates, and tools in the upcoming NFDI service architecture in depth.

The position paper is available on zenodo using the following link:
https://zenodo.org/records/10570654.

Diederichs, Katja
Krause, Celia
Lemaire, Marina
Reidelbach, Marco
Windeck, Jürgen

Tags

NFDI4ING services may be relevant to different users according to varying requirements. To support filtering or sorting, we added a tag system outlining which archetype, phase of the data lifecycle, or degree of maturity a service corresponds to. By clicking on one of the tags below, you can get an overview of all services aligned with each tag.

This service has the following tags:

The tags correspond to:
The Archetypes: Services relevant to Alex – Bespoke Experiments, Betty – Research Software Engineering, Caden – Provenance Tracking, Doris – High Performance Computing, Ellen – Complex Systems, Fiona – Data Re-Use and Enrichment

The data lifecycle: Services related to Informing & Planning, Organising & Processing, Describing & Documenting, Storing & Computing,
Finding & Re-Using, Learning & Teaching

The maturity of the service: Services sorted according to their maturity and status of their integration into the larger NFDI service landscape. For this we use the Integration Readiness Level (IRL), ranging from IRL0 (no specifications, strictly internal use) up to IRL4 (fully integrated in the German research data landscape and the EOSC). Click here for a diagram outlining all Integration Readiness Levels.