Data citation is an invaluable tool of scholarly work. For authors of datasets, it is important that they receive attribution for their work. Citing data also allows readers to locate, access and reuse the data for their own use or for replication.
When citing data, the following components should be used:
Always try to provide as much information as possible.
There is no one standard method for citing data. Many of the data repositories, archives, distributors or publishers have provided their own guidelines to assist researchers.
See also the DOI Citation Formatter from CrossRef
Note: Some sites may require further attribution such as the GES DISC.
Bibliographic & Data Citation Tools
Smith, A., Katz, D., Niemeyer, K., & FORCE11-Software-Citation-Working-Group. (2016). Software citation principles. PeerJ Computer Science. Retrieved from http://doi.org/10.7717/peerj-cs.86.
Green, T. (2009). We need publishing standards for datasets and data tables. OECD Publishing White Paper. Paris: OECD Publishing. Retrieved from http://dx.doi.org/10.1787/603233448430.
Altman, M., & King, G. (2007). A proposed standard for the scholarly citation of quantitative data. D-Lib Magazine, 13(3/4). Retrieved from http://dx.doi.org/10.1045/march2007-altman.
Peter Buneman, "How to cite curated databases and how to make them citable," ssdbm, pp.195-203, 18th International Conference on Scientific and Statistical Database Management (SSDBM'06), 2006. Retrieved from http://homepages.inf.ed.ac.uk/opb/papers/ssdbm2006.pdf.