Further information

Policy of the University of Hohenheim

SInce March 2024 the University of Hohenheim has been an Open Science Richtlinien.

The principles of good scientific practice are the basis for all scientific work and are an essential prerequisite for excellent research. Rules of “Good Scientific Practice”.

Subject-specific recommendations (selection)

On DFG page you will find subject-specific statements that are used in DFG review boards.

More information can be found here (in German): Guidelines and policies

Higher-level recommendations

Advantages of data sharing

Data sharing opens new potential for research and saves resources. If research data is published using national and international information portals, then its faster retrieval can make a significant contribution to the reputational gains of the person producing the data. Scientists’ research becomes more understandable to others and is then reproducible and can be verified.

Another advantage of data sharing is the time and work saved by using well-documented data. This procedure enables a more efficient handling of research findings since they do not have to be collected again. Saving resources and reducing costs are clear advantages, which is why data sharing is also a kind of “resource and knowledge” sharing.

Guides, Links, Tools

Links
  • Licensing of research data:

Creative Commons Licenses 

Open content licenses: Guidelines for the practice

SHERPA/Romeo list gives information about which publishers permit self-archiving.

open-access.net gives information on terms of use

forschungslizenzen.de

  •  Data protection:

Information on data protection law

Does the GDPR apply to your research data?
Interactiv Virtual Assistant 1 : IVA1  (BERD-NFDI)

Lawful consent for data processing
Interactive Virtual Assistant 2: Tool IVA2 (BERD-NFDI)

Fu-Push-Dossier from the Humboldt Universität

Instructions for anonymization  (DIPF)

Informed consent (DIPF)

 Ethical aspects of research data management

 
Manuals

Guidelines on research data management

handbuch.io

Guidelines on RDM - GESIS

finding-citing-documenting

Exercise materials

RDM for agricultural scientists and biologists

RDM in social, behavioral, and business and economic sciences

RDM in geosciences


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