Cite your Data: Persistent Identifiers
Data citation = providing bibliographic reference to data, just like to digital articles and books
Data citation can help by:
- enabling easy reuse and verification of data
- allowing the impact of data to be tracked
- creating a scholarly structure that recognises and rewards data producers
Citing data is important for the recognition of data as a primary research output. Like the citing of text publications it has become part of good scientific practice to refer to data as source. The key to scientific data citation are Persistent Identifiers, in short: PIDs. With a PID your data becomes referable inside research groups and scientific communities and citable in scientific publications.
For citing data especially the PID type Handle and DOI are used. You can request a Handle for a dataset from the GWDG (as part of the ePIC consortium) or a DOI for a dataset for example from DataCite or one of the discipline specific DOI registration services such as the SUB (with a focus on the humanities).
PIDs are not only used to identify digital resources, but can also be used to uniquely identify researchers, which can be quite handy if you have a frequent name or change your name during your research career. ORCID is for example such a PID-system for researchers. Please read our FAQ on PIDs, to learn more about this topic or contact us for further information!
Services at Göttingen Campus
- DOIs: SUB Göttingen acts as a DataCite member in Germany with the focus on digital humanities based on the libraries experiences gathered in historic and current roles for managing Humanities knowledge resources
- Handle: The GWDG hosts a service that offers to create a persistent identifier (PID) to a digital object. The service is part of ePIC, an international collaboration to build a trustworthy high-availability service. ePIC was founded in 2009 by a consortium of European partners in order to provide PID services for the European Research Community, based on the Handle system, for the allocation and resolution of persistent identifiers.
- Ritze, Dominique, Kai Eckert, Magnus Pfeffer. 2013. „Forschungsdaten“. In (Open) Linked Data in Bibliotheken. Berlin, Boston: De Gruyter. DOI: 10.1515/9783110278736.122.
- DOI Handbook
- DARIAH-DE article about PIDs
- DOI FAQ on doi.org