Question

What is data saturation? When in the data collection process or data analysis process can data saturation be identified? How does a qualitative researcher know that he or she reached data saturation?

Answer 1

Data saturation is used as a criterion for qualitative researchers to decipher when data collection or analysis is discontinued — in essence they reach ‘saturation point’. But this is research methodology we’re talking about, so it’s never going to be short and sweet.

From analysing existing literature, we’ve been able to identify four approaches to saturation, which may be either inductive (exploratory — finding patterns of explanations/theories) or deductive (using data to test pre-determined theories)

We identify four distinct approaches to saturation, which differ in terms of the extent to which an inductive or a deductive logic is adopted, and the relative emphasis on data collection, data analysis, and theorizing.

Data saturation of data collection or analysis means that a researcher can be reasonably assured that further data collection would yield similar results and serve to confirm emerging themes and conclusions. When researchers can claim that they have collected enough data to achieve their research purpose, they should report how, when, and to what degree they achieved data saturation.

Data saturation refers to the point in the research process when no new information is discovered in data analysis, and this redundancy signals to researchers that data collection may cease.