Social scientists are awash with new data sources. Though data preprocessing and storage methods have developed considerably over the past few years, there is little agreement on what constitutes the best set of data validation practices in the social sciences. In this paper I provide five simple steps that can help students and practitioners improve their data validation processes. I discuss how to create testable validation functions, how to increase construct validity, and how to incorporate qualitative knowledge in statistical measurements. I present the concepts according to their level of abstraction, and I provide practical examples on how scholars can add my suggestions to their work.
This paper is one of seven published as part of the Policy Analytics Symposium.