Starting your own research from the existing data collected by other researchers can have some major benefits:
However, careful consideration is required before reusing data. Make your search for data as efficient as possible by thinking about the following questions before you get started:
Licenses and user agreements
Methodology
Considering these aspects will help you determine if the data is suitable for you to reuse and help you avoid investing effort and time in analysing data that is unsuitable.
When reusing the data of others, it's critical to give proper attribution to the work of the original creator. This is called data citation and refers to the practice of referencing data to acknowledge it's source, in the same way as referencing a book or journal article.
Citing data is important because it:
However, because the citation of data is a relatively new practice, the standards to follow are often unclear - referencing software like EndNote does have a template for datasets, but other requirements may mean the generated references need to be modified.
Order of precedence:
If these requirements are unclear or informal, DataCite recommends including the following elements (note this follows the APA 7 style guidelines):
Creator(s). (Publication Year). Title. Version. Publisher. ResourceType. Identifier