New Guidelines for Research Data Management: how the ETH Library supports you
Researchers at ETH Zurich are required to employ good practice in managing research data. Learn how the ETH Library supports you in doing so.
The ETH Zurich Executive Board has adopted new DownloadGuidelines for Research Data Management (RDM Guidelines, RSETHZ 414.2). (PDF, 229 KB) These complement the DownloadETH Zurich Guidelines on Scientific Integrity (Integrity Guidelines, RSETHZ 414) (PDF, 233 KB) by specifying further aspects of research data management (RDM). Researchers usually know their community’s practice in handling their research data and many of the processes involved are long established. The new RDM guidelines help ETH Zurich researchers with closing remaining gaps to achieve the best practice in RDM as part of their research.
The ETH Library offers several services and supporting material that assist you with integrating the new RDM Guidelines into your everyday work.
Supporting material that helps you to comply with the guidelines
- Research data and programming code that form the basis of published research output must now be shared according to the FAIR principles. Our Step-by-Step Guide on Data Publication for ETH Zurich Researchers supports you with preparing such research data for publication in a FAIR data repository.
- As of now, all publications of research results from ETH members must contain a Data Availability Statement about where the underlying data can be found. If your journal of choice does not provide a template for it, please refer to the instructions we provide on our Wiki.
- Data management plans (DMP) are now expected for every research project conducted at ETH Zurich which has clear temporal boundaries. We provide instructions as well as a template for preparing a general DMP. If your project is supported by funding agencies (e.g. SNSF), you must of course strictly adhere to their DMP stipulations.
- Agreeing on RDM best practices on the appropriate organisational level contributes to aligning RDM activities. This increases transparency within labs and research groups and facilitates the collection of input, e.g. for a new DMP. A possible form is a data management strategy that supports you in determining common best practices related to RDM in your research group or beyond. For this purpose, we have prepared a guide for the development of a data management strategy.
Good to know: If you publish your research data together with relevant documentation in the ETH Research Collection, you comply with the RDM Guidelines at ETH Zurich.
You will find more general information on RDM at Research Data at ETH Zurich. For information and services from the ETH Library please visit our RDM website and our Wiki for more detailed instructions.
Training and consulting services
In collaboration with other service providers at ETH, we organise regular training such as the ETH Research Data Management Summer School that takes place every year and the semi-annual workshop series on research data management and related topics.
We offer on-demand training for specific topics related to RDM for groups of five people and more. Please contact us at You can use our service for other requests related to RDM, including a review of your DMP.
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