Why we cite datasets and data sources
Spatial datasets, like all datasets, are never raw. Each is the result of several decisions, priorities, and constraints. They are authored and edited.
As a result, we cite datasets for two related reasons:
First, our work builds on the work that came before: we cite to credit data creators, acknowledging the labor (intellectual and otherwise) required for a dataset’s making. This is the usual reason for remembering to cite your sources. It avoids plagiarism that is a foundational part of maintaining integrity in the work.
Second, again, our work builds on the work that came before: we cite to disclose (and remind ourselves of) the embedded perspectives, agendas, limitations, and histories that all datasets carry, acknowledging that these directly influence our work and our findings.
Data citations are no different than those for books, journal articles, maps, and films. While spatial data citations formats have not been as widely standardized, they should include the same standard information you would use for other citations: Author, title, date (including revisions), publisher, and URL if found online.