Data Management Services

We – Aliya Nauroth-Kreß and Barbara Bärthlein – are part of the department of "IT for Research and Management" at the Medical Center for Information and Communication Technology (MIK-IFM) at the University Hospital Erlangen. Our goal is to offer competent and collaborative support for all challenges related to your research data.

We are here to assist you from the initial planning of your project through the application process to the successful implementation of your research endeavors. We provide advice and support in all aspects of research data management (RDM), requirements from funding agencies, and the selection of suitable tools and services to help you make your projects efficient and successful. Furthermore, we offer various Services & Tools to support you with the RDM of your projects and provide Trainings & Events that can impart the necessary RDM skills. Don’t hesitate to get in touch with us about this.

In science, large amounts of diverse data are constantly being generated. Especially over the last ten years, the volume of this data has increased significantly due to new scientific methods. All data collected or generated during scientific work is referred to as research data, regardless of the data type.

To fully facilitate research data and exploit their full value, structured data management is essential. Additionally, in the scientific context, the reuse of data plays a major role. Reuse of data refers to re-evaluating data that has already been collected in other projects to gain additional insights or validate results. This can be done by the original creators or by other researchers. The entirety of managing research data, as well as providing them for reuse and reproduction of results, is referred to as Research Data Management (RDM).

Many research projects are funded by government agencies or nonprofit organizations. Thus, the resulting data is considered public property and should therefore be made freely available whenever possible. This demand is mirrored in the guidelines of most research funding agencies, which require RDM following the FAIR Principles.

FAIR stands for "Findable", "Accessible", "Interoperable", and "Reusable". The FAIR Principles were developed to describe how research data should be handled to facilitate successful and sustainable research. Only if data is findable other researchers can incorporate them into their thinking, theories, and projects. A solution to make studies and their corresponding datasets findable, even if the data itself cannot be shared, are study registries, such as the one we host at UKER. To use research data to reproduce results or to reevaluate them in other research projects they need to be acessible as well. For example, data can be made available for other researchers through public repositories like Zenodo. If research data is only available in vendor-specific formats (e.g., specialized microscopy formats), it may only be usable with proprietary software from the vendor. If the vendor discontinues support for the software, such data may become entirely unusable. Therefore, data should be interoperable, which can be achieved by transforming the data to an open data format and providing necessary documentation. However, even interoperable research data can be worthless without sufficient context. To make data reusable, it is also important to consider the context of the research project in which they were collected. Thus, data must be saved together with metadata. Metadata is additional information that describes the actual research data, ranging from details such as author and title of a study to detailed information about the variables used in a study.

Research Data Management includes the planning and implementation of measures that make research data FAIR, thus actively supporting research.

The data lifecycle model describes the various stages that research data can go through. It can be presented in different levels of detail and varying structure, but typically includes six elements: planning, collection, analysis, publication, archiving, and reuse. Each of these elements involves different measures. The data lifecycle helps to stay on top of things and facilitates the implementation of targeted research data management.

• Advice on the requirements of research funders
• Support in implementing RDM in your research projects
• Guidance on reusing external data in your projects
• Assistance in creating a data management plan
• Advice on and recommendations for suitable tools for RDM in your projects
• Access to services and expert teams at University Hospital Erlangen (UKER)
• Tailored workshops to suit your needs

The first consultation is free of charge. Further support or more extensive consultations include costs depending on the scope and type of tools and services required.

We look forward to supporting you and working together to make your projects a success!