Research Data Management

Scientific research requires a structured approach to research data. Research data management (RDM) is based on the data lifecycle and encompasses all processes—from planning to long-term storage:

• Planning research projects
• Collecting data
• Processing and analyzing data
• Storing and archiving data
• Sharing and making data available
• Reusing data

You can find an explanatory video (3:38 minutes) on RDM from the project FDM-ndsHAW in German here.

We provide support, advice, and training on all aspects of RDM. Contact us.

For additional research support, visit the website of the Science Support Hub.

Research data refers to all data generated during research processes or reused for other purposes. Examples include:

• Measurement data
• Laboratory results
• AV material
• Survey data
• Texts, corpora
• (Digital) objects from collections or samples
• Methodological testing procedures (questionnaires, software, simulations), etc.

You can find an explanatory video (3:23 minutes) on research data from the project FDM-ndsHAW in German here.

The FAIR data principles (Findable, Accessible, Interoperable, Reusable) help ensure that research data is accessible and reusable. They are part of the Good Research Practice.

You can check the FAIRness of your research data using the FAIR Assessment Tool from TKFDM, among other tools.

Closely related to FAIR are the CARE Principles for Indigenous Data Governance, which stand for Collective Benefit, Authority to Control, Responsibility, and Ethics.

A Data Management Plan (DMP) outlines all measures related to research data—from collection to reuse. A DMP supports researchers in their collaboration and documents this process. This ensures that the data remains accessible, usable, and traceable—in accordance with the FAIR Data Principles. DMPs can be created using the tool RDMO.

You can find an explanatory video (2:39 minutes) on DMPs from the project RDM-ndsHAW in German here.

For many research funding agencies, the DMP is a component of the proposal and is sometimes considered part of the research results. They often cover the costs of RDM, but these must be factored in beforehand. It is best to start planning as soon as your research project takes shape. Please feel free to contact us before finalizing your funding proposal.

Software Management Plans (SMPs) help ensure that software is designed to be reusable and sustainable in accordance with the FAIR Principles for Research Software (FAIR4RS Principles). More information is available in the Practical Guide to Software Management Plans (1.1). You can find a sample SMP at the Max Planck Digital Library, among other places.

In accordance with the Good Research Practice, research results should be retained for at least 10 years. Suitable venues for publication include research data repositories, research data centers, data journals (data papers), or publication as a data supplement. An overview is available at re3data.org.

The University of Hildesheim offers the research data repository HilReDa.

The University of Hildesheim provides its members with services and tools to support them in managing research data. All you need is your UNI account from the Rechenzentrum.

• HilReDa: University of Hildesheim Research Data Repository
• HilData: Digital Asset Management System, including the provision of (sensitive) research data
• Overview of file storage options

Additional services are offered by the Methodenzentrum, the Servicestelle digitale Lehr-Lernformate (SdLL), Qualitätsmanagement, and the Rechenzentrum, among others. In addition, there are subject-specific services and tools from third-party providers, including for sensitive data. We are happy to advise you on your selection and support you in using these resources.

For support regarding technical and infrastructure services, please contact the Rechenzentrum or inquire at your research institute (overview).

Throughout the course of a research project, many legal aspects—such as copyright and usage rights—must be addressed. Data protection must be taken into account, particularly when working with personal and sensitive research data.

Working with research data touches on many areas of research ethics. These include the Good Research Practice, as well as research involving or conducted on vulnerable groups or using human material.

For questions regarding research ethics at the University of Hildesheim, contact the Senate Ethics Committee or the Ethics Committee of Faculty 1.

The Guidelines for the handling of research data at the University of Hildesheim were adopted by the Extended University Management on February 5, 2020. They provide researchers of the University of Hildesheim with a framework that ensures transparency, clarity, and support in the handling of research data. These guidelines were developed in response to the requirements of research funding agencies such as the DFG, BMFTR, and the EU regarding the handling of research data.

You can find a Learnweb course on research data management in German here.

Additional materials are available in the Zenodo community Research Data Management University of Hildesheim (FDM@UHi).

• State Initiative Research Data Management Lower Saxony, Contact: info[at]fdm-nds.de
• forschungsdaten.info
• researchdata-education.de
• forschungsdaten-bildung.de
• Nationale Forschungsdateninfrastructur (NFDI)
• Specialized Information Services (German: Fachinformationsdienste, hence FID) (Overview)

Please send us any questions by email.