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Traditionally, the only citations within scholarly writing are to other scholarly writing. In some Journals today, URLs are allowed as footnotes, but not typically as full-fledged references within citations. This is for good reason. URLs are notoriously ephemeral, and URLs pointing to data have half-lives of less than a decade \cite{Pepe_2014}.   A great deal of public scholarly worrying (and writing) about how to offer robust, long-lived, links to data has gone on over especially the past decade (\citet[][and (\cite[][and  references therein]{Goodman_2014}). Here, we will just offer the following practical advice. **If a dataset can be assigned a long-term identifier that moves with data as it moves from one computer system to another, then such an identifier should be sought, and it should be cited in scholarly articles**. One modern version of such "persistent" identifiers are "DOIs" which use the so-called ["Handle"](http://www.handle.net) system. Details on how this system works are here: http://www.doi.org/factsheets/DOIHandle.html. There are currently several systems that will issue DOIs when data are uploaded to a repository, including Zenodo, figshare, and the Dataverse. Each system presently has different various advantages and disadvantages, concerning ease-of-use, richness of metadata, formats accepted, but what matters to authors and Jornal publishers is that any of these systems will issue a robust DOI for a data set that can be included as a so-called "first class" reference (like citing a Journal Article) in scholarly writing. Any modern scientific publication should adjust its practices to accept these DOIs as references, and it should encouage authors to seek these DOIs.