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The GFBio Data Center Recommendation Tool (DCRT)

The GFBio Data Center Recommendation Tool (DCRT) supports you in finding a suitable data center for your research data and making your data FAIR (Findable, Accessible, Interoperable, and Re-usable).

Within the GFBio consortium, nine data centers, specialized in their research fields, are implied. Depending on the data you collected, the tool recommends one or several data center(s) which meet your requirements best. If you collected different kinds of data, you can run the tool for each one of them. If you need further support in choosing a suitable data center, you can find a general GFBio contact beneath the data center recommendation list. Our experts will help you to find your best suiting data center and will also provide their expertise for a successful submission of your research data.

Data Center Recommendation Tool

Do you want to submit physical objects along with your data?
Is your object dead or alive?
Is your object taxon-based?
Do you have mainly sequence data?
Please select a category
Which kind of material would you deliver?

Data Center Recommendation

Do you need support in selecting a suitable data center or do you have further questions concerning data management?
Please use our generic submission or get in contact with us:

German Federation for Biological Data (GFBio)


Data centers offer curation and preserving (archiving) of research data as well as data publication which makes your data citable, e.g. by attaching a DOI.

The organization and description of data as well as the accumulation of ontologies are data curation processes. A detailed description (documentation) of your data set needs to be provided, so other users can easily find your data, understand the context and content, re-use it and cite it. The description of data generates structured information, the so-called 'metadata'. For more information, please see Data Life Cycle - Describe.

Preserving (archiving) digital content is more than backing it up. It is a set of actions, which ensure long-term retention of the integrity of data by maintaining its (a) accessibility, (b) authenticity and (c) longevity. Digital objects are fragile, being susceptible to "data rot" which might influence their accessibility and authenticity. For more information, please see Data Life Cycle - Preserve.

Data publication refers to the publication of a data set linked to a research publication of the related results. Data are publicly available, citable and uniquely identifiable via a persistent identifier (PID, e.g. DOI). This is based on the fact that data are a fundamental part of the research process and as important as the discussion and the conclusion derived from them. Furthermore, the publication of data sets promotes transparency in the research life cycle, facilitates the verification and reproducibility of results, and very likely increases your citation rate. For more information, please see Data Life Cycle - Publish.