Data Quality in Social Survey Research

Social survey researchers need to share criteria for assessing the quality of data. In the tradition of data quality debate, two antithetical positions emerge. One comes from the behaviourist paradigm: the quality of survey data is defined as the absence of distortions in the measurement process. The other was born within the pragmatic paradigm: data quality is the satisfaction of the logical and methodological conditions necessary to achieve the cognitive objectives of the research. The first position largely prevails, but the pragmatic one is more adequate because it looks at the actual research conditions that move the social survey research. This approach rejects the concept of true value; the data of survey research is constructed by the researcher's choices. This article explores the survey data quality in its pragmatic perspective, offering definitions of conceptual map, conversational interview, data fidelity, data quality, formal standardization, semantic standardization, social desirability, response accuracy, pretest, and validity.