A data collection is a coherent group of data that relate to each other in identifiable, describable ways and represent a stand-alone resource that could be analytically useful for scholars beyond the scholar who collected/generated the data. A data collection has some categorization or logic that makes the data more than just an aggregation of used materials.
Data collections vary widely in structure. For instance, they may contain formalized information gathered in the context of pre-set categories and come in the form of a preconfigured database (i.e., may have rows and columns), or may be a particular group of documents or a specific set of interview transcripts. They may contain many different types of data, and may include data relevant to different aspects of a research project (some data may measure a variable, other data may be used for process tracing, representing a sequence of information leading up to an outcome). The key is that the logic that connects them can be elucidated.
In order for QDR users to get an idea of just one form that a data collection might take, we direct them to a pilot project by Diana Kapiszewski, “The Argentine Supreme Court in Press, 1995-1999", a database of almost 2,000 newspaper articles addressing Argentina’s highest court drawn from the country’s preeminent national newspaper, La Nación.