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Guidelines for managing research data at Leibniz Universität Hannover

Research data management is currently a widely discussed issue, but how can it be integrated into every day scientific working?

The following overview may help you planing your data handling from the very start. Effectively organizing your data will keep it re-usable on the long run.

Work in progress - missing contets of this site will be translated soon (hopefully..)

FAQ on research data management

What is meant by “research data”?

Research data is generated and processed in the course of scientific working and constitute the basis for research results. Data types are diverse. They may comprise measurements, secondary analyses, visualisations, models, and the results of polls and surveys. The formats of files holding numbers, text, code, or graphics are manifold as well.

Why should I keep research data?

It is good scientific practice to keep at least the data published works are based on for no less than ten years. You should make as much data publically accessible as possible in order to facilitate its reuse and the validation of research results. This measure is also increasingly demanded by many funders and big international journals.

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

You should discuss data management with your team right from the start of a long-term project. The discussion results can then be fixed in form of a first data management plan which can and should be completed and updated whenever the need arised. This not only facilitates a later reuse of the data but also its initial processing and analysis. Rules for a systematic structuring and naming of files should be part of the plan as well as safety and privacy issues, access rights, and backup strategies. When publishing data sets make sure they get a unique identifier, such as a Digital Object Identifiers" (DOI), which ensures that it can be cited properly on the long run. You can find detailed How-To-guides in the section Dokumente und weiterführende Links.

Where do I get advice and support?

Managing research data comprises more than just keeping it! Leibniz Universität Hannover is extending and improving IT-infrastructure along with counselling services and training courses in order to support its scientific staff at managing data. All services are listed here. If you have any questions regarding research data management feel free to contact Volker Soßna at Dezernat 4 anytime or write to forschungsdaten(at)uni-hannover.de. Helpful links and further reading are listed here.

What is meant by “research data”?

Research data is generated and processed in the course of scientific working and constitute the basis for research results. Data types are diverse. They may comprise measurements, secondary analyses, visualisations, models, and the results of polls and surveys. The formats of files holding numbers, text, code, or graphics are manifold as well.

Why should I keep research data?

It is good scientific practice to keep at least the data published works are based on for no less than ten years. You should make as much data publically accessible as possible in order to facilitate its reuse and the validation of research results. This measure is also increasingly demanded by many funders and big international journals.

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

You should discuss data management with your team right from the start of a long-term project. The discussion results can then be fixed in form of a first data management plan which can and should be completed and updated whenever the need arised. This not only facilitates a later reuse of the data but also its initial processing and analysis. Rules for a systematic structuring and naming of files should be part of the plan as well as safety and privacy issues, access rights, and backup strategies. When publishing data sets make sure they get a unique identifier, such as a Digital Object Identifiers" (DOI), which ensures that it can be cited properly on the long run. You can find detailed How-To-guides in the section Dokumente und weiterführende Links.

Where do I get advice and support?

Managing research data comprises more than just keeping it! Leibniz Universität Hannover is extending and improving IT-infrastructure along with counselling services and training courses in order to support its scientific staff at managing data. All services are listed here. If you have any questions regarding research data management feel free to contact Volker Soßna at Dezernat 4 anytime or write to forschungsdaten(at)uni-hannover.de. Helpful links and further reading are listed here.