Granting access to data requires the data to be well-documented, properly organized and stored, licensed (Creative Commons, for example), easily identifiable (DOI), and preserved for the long term.
There are many benefits to sharing data, including:
Citing data properly is essential in order to:
A dataset should be cited formally in an article's reference list, not just informally in the text. Many data repositories and publishers provide specific instructions for how to cite their data. If no citation information is provided, you can use generally agreed- upon guidelines. DataCite Metadata Schema is an example.
There are 5 core elements of a dataset citation, with additional elements added as needed.
Although the core elements are sufficient in a simple citation (ie.: citation to the entirety of a static dataset), some additional elements may be needed if you are citing a dynamic/evolving dataset or a subset of a larger dataset. These include:
A final, important step is obtaining a persistent, unique identifier for the dataset (a digital object identifier, or DOI, for example). Unique identifiers facilitate easy citation of data and allows usage statistics to be tracked.
Public data identifiers should be: