FAQ on research data management

  • What is meant by "research data"?

    All data generated and processed in scientific activities are considered research data. They constitute the basis of the research results. Data types can be quite diverse and may comprise measurements, secondary analyses, visualisations, models, and the results of polls and surveys. Equally manifold are the file formats used to hold numbers, text, code, or graphics.  Even physical samples such as minerals or tissues are sometimes defined as "data".

  • Why should I keep research data?

    It is good scientific practice to keep at least those data underlying published works for no less than ten years. If as many data as possible are also made publically accessible, they can be re-used in further projects. Also scientific results are easier to validate. This is why funders and important international journals increasingly demand that research data are not only kept but also published.

  • What do I have to keep in mind when managing my data?

    When starting a project, you should thoroughly think about how you want to handle your data and write down the results in a data management plan. Important points to be addressed are, for example, the administration and documentation of files, storage capacities, security issues and backup strategies. Anticipation will pay when processing and analysing data in the course of a longer project. When publishing datasets make sure they get a unique identifier, such as a  "Digital Object Identifier" (DOI) to make it citable. You can find a template for a data management plan in the publications section.

  • What information on research data management has to be in the funding application?

    The extent to which you have to provide information on the handling of research data depends on the respective call, your subject and the type of data collected in your project. In any case, you should explain how you ensure that your data is kept for at least ten years in accordance with good scientific practice (recommendation 7). The sponsor generally also expects you to make your research data publicly available when a project ends, provided there are no legal constraints (such as data protection, patent law, contractual agreements with industrial partners, etc.). The publication of data, in turn, requires their appropriate preparation.

    We have compiled more detailed information on the topic under Funding Applications. If you would like personal advice, please contact the research data support team. For DFG proposals, it is also worth taking a look at the document Research Data Management in DFG Proposals: What can, what should, what must be described? (German only)

  • Which costs can be incurred for research data management?

    The extent to which costs for research data management measures arise is different in each project. Two example calculations can be found here. Important influencing factors are the volume of data, the number of files and the degree of homogeneity. The more manual work is required, the higher the labor requirement and thus the costs. The publication of data is free of charge in many repositories. However, larger volumes of data or the use of additional services (such as data preparation and curation) may incur costs.

  • Where do I get advice and support?

    If you have any questions regarding research data management feel free to contact the Service Team at Dezernat 4 anytime or write to forschungsdaten(at)uni-hannover.de. Helpful links and further reading are listed here. Please contact the Data Protection Office, if you have any questions regarding the handling of personal data.