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Humboldt-Universität zu Berlin - Research data management

Cite research data

Please notice the following advice for the citation of research data.

Practical recommendations for the citation of research data can be found at Research data citation.

 

FORCE11 Data Citation Principles

The Data Citation Principles of FORCE11 cover purpose, function and attributes of citations. The following principlesrecognize the dual necessity of creating citation practices that are both human understandable and machine-actionable.

The following citation principles are not comprehensive recommendations for data stewardship. As practices vary across communities and technologies will evolve over time, no recommendations for specific implementations are included; communities are rather encouraged to develop own practices and tools that embody these principles.

The principles are grouped so as to facilitate understanding, rather than according to any perceived criteria of importance.

  1. Importance

    Data should be considered legitimate, citable products of research. Data citations should be accorded the same importance in the scholarly record as citations of other research objects, such as publications.

  2. Credit and Attribution

    Data citations should facilitate giving scholarly credit and normative and legal attribution to all contributors to the data, recognizing that a single style or mechanism of attribution may not be applicable to all data.

  3. Evidence

    In scholarly literature, whenever and wherever a claim relies upon data, the corresponding data should be cited.

  4. Unique Identification

    A data citation should include a persistent method for identification that is machine actionable, globally unique, and widely used by a community.

  5. Access

    Data citations should facilitate access to the data themselves and to such associated metadata, documentation, code, and other materials, as are necessary for both humans and machines to make informed use of the referenced data.

  6. Persistence

    Unique identifiers, and metadata describing the data, and its disposition, should persist - even beyond the lifespan of the data they describe.

  7. Specificity and Verifiability

    Data citations should facilitate identification of, access to, and verification of the specific data that support a claim.  Citations or citation metadata should include information about provenance and fixity sufficient to facilitate verfiying that the specific timeslice, version and/or granular portion of data retrieved subsequently is the same as was originally cited.

  8. Interoperability and Flexibility

    Data citation methods should be sufficiently flexible to accommodate the variant practices among communities, but should not differ so much that they compromise interoperability of data citation practices across communities.

 

Thomson Reuters Data Citation Index

The Data Citation Index of Thomson Reuters is an online database and available at the Web of ScienceTM platform. The Data Citation Index simplifies the discovery, use and allocation of research data and connects the data with related literature. The delivery of metadata to Thomson Reuters is inter alia a result of a Digital Object Identifier (DOI) registration via DataCite.