General, including qualitative:
When possible, check the style manual or guide for the citation style you are using. If it does not include information for citing data or datasets, use the information below to generate a citation.
Whether you produced the data yourself or you're using someone else's data in your research, it is important to maintain a linkage between your paper and the supporting datasets by citing them. This gives credit to the person who created the data and enables others to reproduce the research and verify results. For additional information, see ICPSR 101: Why Should I Cite Data.
There are many challenges in citing data. In many disciplines, there are no clear instructions on how to cite data, and many major style guides (APA, NLM, etc.) do not give specific guidance to address data/dataset citation. Additionally, data is often not recognized as a format in citation managers, so you may have to create the citation manually. Some datasets are dynamic, which can further complicate how and what to cite. However, some data repositories will suggest a citation. When there are no specific instructions for citing data, you may need to adapt instructions for a similar format, such as an electronic resource or web page.
Try to include these elements of the dataset in your citation:
Some dataset distributors provide a checksum to ensure that the dataset hasn't been changed or corrupted since it was published, and this may be included in a source note. Other important information for understanding and using the dataset may be included in supplementary files (e.g., codebook, readme.txt) available at the same link as the citation or in the source notes of the paper.
Adapted from Citing Data, Michael Witt, Purdue University Libraries