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Publishing data

Research data, the basis for scientific publications, can be published and considered as independent research output. Publishing research data allows to validate, replicate and further develop research results. New collaborations or hypotheses can emerge, and duplication of work can be avoided.

There are basically two ways to publish data: in repositories or as a supplement to scientific articles. In addition, it is also possible to publish a descriptive data article in a data journal.

 

Repositories

The most common way to publish research data is to use a repository.

Research data repositories are central systems for storage, archiving and reuse of research data. Their functions include secure storage of data, assignment of DOIs and other identifiers, establishment of embargos as well as collection of informative metadata.

There are different types of repositories: generic, discipline-specific and institutional repositories. Suitable generic and discipline-specific repositories can be found via platforms like re3data.org, fairsharing.org or RIresources.

Discipline-specific repositories are suitable for publications from a specific field or multiple, often adjacent, fields. They offer a particularly high discoverability of research data within the respective discipline.

Examples for discipline-specific repositories:

Generic repositories are open for all research fields and typically allow to publish research data as well as software, video material, presentations and more.

Examples for generic repositories are:

  • Zenodo
    The service is financed by the European Commission and managed by the OpenAIRE consortium and CERN.
  • Figshare
    A commercial repository by the Holtzbrinck Publishing Group. HHU does not offer an institutional access.
  • Dryad
    Generic repository with focus on research data from the life sciences.
  • OSF (Open Science Framework)
    Platform for managing, publishing and archiving research projects and data.

Institutional repositories are operated by universities or research institutions and are usually only available to members of these institutions.

An example is the institutional repository HHU ResearchData, which is freely available to all employees and researchers of HHU. Research groups and projects can publish research data - up to a limit of 1 TB - with automatic DOI assignment. By setting up an embargo, data can be made publicly accessible after a specified time period.

Data as Supplement and Data Journals

Further possibilities for the publication of research data are the publication as a supplement or the publication in a data journal.

Research data can be published as a supplement of a scientific article. There are two possibilities to realize that:

  • Data is published as an appendix, mostly in PDF format, together with the article.
  • Data is published independent of the article, for example, in a repository.

In the first case, publication as an appendix, the data does not get a persistent identifier and is not seen as an independent research output. It does not get a DOI and is not available in Open Access if the article itself is not published in Open Access.

In the second case, publication via a repository, the data gets a persistent identifier (e.g., a DOI) and is seen as an independent research output. The associated article includes information on where and how to access the data, i.e., the data is explicitly cited.

Data journals offer the possibility to publish articles which describe data next to the classical publications where data is interpreted.

As for classical journals, data journals can also be peer-reviewed. They can be Open Access journals or classical, closed access journals.

The data itself is typically available via a repository with its own persistent identifier (e.g., DOI). The associated article includes information where the data can be found.

Some examples for data journals are:

 

 

Your way to publication

You would like to publish your data and have questions? Write us at fdm(at)hhu.de.

In general, the following aspects should be taken into account when publishing data:

  • choose a suitable discipline-specific repository,
  • decide on license, data format and metadata standard,
  • check possible copy right restrictions,
  • check possible data protection restrictions, if applicable pseudonymize or anonymize the data,
  • check data transfer and data usage agreements.

 

If you have question with respect to copy right or data protection issues, please contact HHU Staff Unit Legal Affairs or Data protection Unit.