Research data under control at the UW/H
Why every research process needs a data management plan - even at Witten/Herdecke University.
What this article is about:
- why data management plans (DMPs) are useful for all researchers,
- which tools and infrastructures support their creation, and
- what role the DMP4NFDI basic service plays in this.
Data management plan useful for all researchers
For many, a data management plan initially sounds like additional bureaucracy. In reality, it is one of the strongest levers for setting up projects properly - even for researchers at UW/H.
A data management plan, or DMP for short, is the centrepiece of professional research data management. It sets out how research data is created, structured, securely stored, shared with others and archived in the long term throughout the course of the project.
A good DMP supports researchers in working more efficiently, complying with legal requirements and making research results open and traceable. At the same time, it helps the institution to establish standards and provide resources (e.g. storage, consulting, infrastructure) in a targeted manner.
The Research Data Management Organiser (RDMO) on the forschungsdaten.info platform also provides UW/H researchers with a web-based service for planning, documenting and creating data management plans. A structured interview guide helps to systematically record all important aspects of data management.
The DFG has also created a detailed checklist for handling research data, which can serve as the basis for a DMP. In addition, information on research data management is mandatory in DFG proposals.
The UW/H intranet also provides helpful arguments for writing DMPs:
https://intranet.uni-wh.de/lehren-forschen/uw/h-forschungsdatenmanagement/ueberblick/datenmanagementplaene
The topic of DMPs is therefore regularly present in the structured doctoral colloquia, doctoral programmes and academic introductory events at the UW/H.
Data management plan tools (infrastructures)
Chairs can decide which tool they want to use depending on their needs - for example RDMO or initially the DFG checklist. There are recommendations, but no fixed requirements.
The tools make an important contribution: they facilitate the documentation of research processes, help to record metadata in a structured manner and promote interoperability. In this way, they create order in an area that can quickly become confusing.
Modern DMP tools are designed to capture information in a machine-readable format. This enables, for example
- automatic examinations,
- links to repositories or electronic lab books,
- the reuse of metadata and
- integration into existing workflows.
DMPs thus become active building blocks in the research process and not static documents - as is the case with the RDMO tool:
https://rdmorganiser.github.io/
About the DMP4NFDI basic service
In summer 2024, the DMP4NFDI basic service began its work to further develop data management plans (DMPs) specifically for the consortia of the National Research Data Infrastructure (NFDI).
The service establishes a central infrastructure for DMPs within the NFDI and supports the consortia in the creation and provision of standardised DMP services. In the initialisation phase, the NFDI DMP Template Framework, which is based on the de facto standard for machine-actionable DMPs, is being developed together with pilot consortia.
The technical basis is a multi-client-capable RDMO instance. It enables the NFDI consortia to use their own, flexibly customisable clients and at the same time benefit from a centrally operated infrastructure.
The aim is to further increase efficiency and interoperability in research data management.
Contact research data management
Annette Strauch-Davey, M. A.
Scientific representatives with teaching duties
Faculty of Health | Faculty Office
Alfred-Herrhausen-Straße 50
58455 Witten