With standardized file naming and versioning, researchers can keep track of their research data. Standardized structures save time and effort. Regular backups minimize the risk of data loss. Well-documented data can be reused in other research contexts after the research project has been completed.

You should budget around 5% of the total project funding for research data management. You can often apply for funding directly from third-party funding providers (project application, see funding guidelines of third-party funding providers).

When storing data, security measures must be taken to prevent unauthorized persons from gaining access to the research data. Please contact the UW/H's RDM Service Center, which cooperates with the Data Protection Officer in this regard.

• iva1: Decision-making aid on the applicability of the GDPR (browser-based tool from BERD@NFDI)
• iva3: Decision-making aid on the applicability of legal bases with research privileges (browser-based tool from BERD@NFDI)

Anonymization tools help to anonymize research data:

• Qualiservice anonymization tool QualiAnon
• Amnesia anonymization tools from OpenAIRE
• ARX Data Anonymization Tool

• Research data can be published as a supplement to a specialist article published by the publisher, e.g. aggregated research data such as images or tables.
• Research data can be published as an independent information object in a repository. There are different types of repositories:
  •  Institutional repository: it is a document server operated by institutions, e.g. by a university or in associations
  •  Discipline-specific repository: it is a repository specialized in a scientific discipline or a specific subject area
  •  Generic repository: it is open to all scientific disciplines, see Zenodo.

The question must be re-examined in each case (content and collection of data, structure of the project and data storage, property rights, copyright). Please contact the RDM Service Center, which cooperates with the data protection officer of UW/H.

Research data centers (RDCs) can provide access to sensitive data that cannot be published freely due to restrictions. As part of a nationwide sustainable research infrastructure, Germany currently has a network of 41 research data centers accredited by the German Data Forum (Rat für Sozial- und Wirtschaftsdaten, RatSWD): https://www.konsortswd.de/angebote/forschende/alle-datenzentren/

(Publication: Fuß, D., & Schlücker, F. (2025). Recommendation of the FDI Committee for a uniform designation of data products of research data centers (KonsortSWD Working Paper No. 11). Consortium for the Social, Behavioral, Educational and Economic Sciences (KonsortSWD). https://doi.org/10.5281/zenodo.1489970

The anonymization of personal data is part of good scientific practice. The BDSG (Federal Data Protection Act) § 3, para. 6 defines anonymization as all measures that change personal data in such a way that “the individual details about personal or factual circumstances can no longer be assigned to a specific or identifiable natural person, or only with a disproportionate amount of time, cost and manpower”.

BERD@NFDI deals with the integrated management of algorithms and data across the entire research cycle. The focus is on unstructured data (video, image, audio, text or mobile data and big data): https://www.berd-nfdi.de/

In order to ensure the reusability of research data, the granting of additional rights of use should be considered, e.g. by licensing the research data. The use of Creative Commons (CC) licenses is one way of defining conditions for the reuse of published research data.

Overall management of data availability, usability, integrity and security.

DH.NRW is "a cooperative association of 42 universities with the Ministry of Culture and Science. The core concerns of this association are the improvement of study opportunities, the enhancement of study and teaching quality and the support of academics in the context of digital transformation." Information can be found here: https://www.dh.nrw/

A Digital Object Identifier (DOI) is a persistent identifier of digital objects. The DOI remains the same over the entire lifetime of a designated object. DOIs are assigned via repositories upon storage and directly before publication, e.g. for good referencing.

The aim of long-term archiving is to enable access to archived data over a long period of time.
See also here: Strauch, A., Hess, V. (2019). From production to long-term archiving of qualitative research data in the CRC 1187. BIBLIOTHEK - Forschung und Praxis, 2019, https://doi.org/10.1515/bfp-2019-2005

An ELN - Electronic Laboratory Notebook - is software that can be used to record the life cycle of research data. Examples of open source ELNs include the following: Chemotion (from NFDI4Chem), eLabFTW for experimental sciences or openBIS (from ETH Zurich) for the life sciences. The Technical University of Darmstadt has created the ELN Finder, which we use to search for suitable lab notebook software.

The European Open Science Cloud (EOSC) is a European Commission project that supports research data management at European level: https://research-and-innovation.ec.europa.eu/strategy/strategy-research-and-innovation/our-digital-future/open-science/european-open-science-cloud-eosc_en

At best, a research data policy is a guideline that guarantees researchers support in research data management at the university and provides recommendations in accordance with good scientific practice.

"The state initiative fdm.nrw is the central coordination office for bundling and strategically developing RDM activities within DH.NRW. The aim of fdm.nrw's work is to link the universities in NRW with the developments of the National Research Data Infrastructure." (https://www.mkw.nrw/themen/wissenschaft/wissenschaftspolitik/forschungsdatenmanagement-fdm-den-hochschulen)

"As a secure national omics data infrastructure, GHGA enables the use of human omics data in research. At the same time, we attach great importance to data security to ensure that sensitive information is handled responsibly." Further information can be found here: https://www.ghga.de/de/

Identity and access management for the NFDI: "Identity and access management (IAM) deals with the processes, policies and technologies for managing digital identities and their access rights. A central goal of the NFDI is to enable uniform access to data, software and computing resources as well as sovereign data exchange and collaborative work. To achieve this, it is planned to connect and expand existing and emerging IAM systems in such a way that researchers from different fields and institutions can access digital resources within the NFDI as easily as possible." (Application of the basic service)

"The Local Data Hub (LDH) serves to present and exchange your projects, studies, publications, (bio)medical data, models and software tools from the field of health research and is based on the FAIR principles (Findable, Accessible, Interoperable, Reusable). Target groups are researchers from the fields of (bio)medicine, epidemiology, biostatistics, modeling or bio- and medical informatics. The LDH is an easy-to-manage, web-based software solution that can be operated directly and securely encapsulated in your network." (See NFDI4Health: Local Data Hub - a service of NFDI4Health)

The Jupyter-Notebooks application is used for various tasks in dealing with research data (data analysis and visualization, statistical modeling, machine learning, deep learning). Jupyter4NFDI is working on offering a centralized service (support of FAIR Digital Objects (FDOs).

"The National Research Data Infrastructure (NFDI) is intended to systematically develop, sustainably secure and make accessible the data stocks of science and research and to network them (inter)nationally. It will be established as a networked structure of consortia acting on their own initiative in a process driven by the scientific community." See here on the DFG website: https://www.dfg.de/de/foerderung/foerderinitiativen/nfdi

"NFDI4Health - the National Research Data Infrastructure for Personal Health Data - focuses on data generated in clinical, epidemiological and public health studies. The collection and analysis of this data on health and disease status and important influencing factors are an essential component for the development of new therapies, comprehensive care approaches and preventive measures in a modern healthcare system." (https://www.nfdi4health.de/)

Open access means barrier-free access to scientific content. Users are granted usage rights and simple access paths so that scientific information is shared and reused. Open Access is part of the Open Science movement.

PID4NFDI is a basic service for persistent identifiers (NFDI) that is currently being developed. The basic service is currently in the integration phase (as of April 2025). Persistent identifiers (PIDs) are central to FAIR research data management.

Providing a federated architecture of terminology service components and enabling interoperability between different disciplines is the goal of TS4NFDI to build common knowledge representation and knowledge development frameworks for the NFDI communities.